Environmental problems caused by plastic waste have been continuously growing around the world, and plastic waste is increasing even faster after COVID-19. In particular, PP and PE account for more than half of all plastic production, and the amount of waste from these two materials is at a serious level. As a result, researchers are searching for an alternative method to plastic recycling, and plastic pyrolysis is one such alternative. In this paper, a numerical study was conducted on the pyrolysis behavior of non-condensable gas to predict the chemical reaction behavior of the pyrolysis gas. Based on gas products estimated from preceding literature, the behavior of non-condensable gas was analyzed according to temperature and residence time. Numerical analysis showed that as the temperature and residence time increased, the production of H2 and heavy hydrocarbons increased through the conversion of the non-condensable gas, and at the same time, the CH4 and C6H6 species decreased by participating in the reaction. In addition, analysis of the production rate showed that the decomposition reaction of C2H4 was the dominant reaction for H2 generation. Also, it was found that more H2 was produced by PE with higher C2H4 contents. As a future work, an experiment is needed to confirm how to increase the conversion rate of H2 and carbon in plastics through the various operating conditions derived from this study's numerical analysis results.
Journal of the Korea Academia-Industrial cooperation Society
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v.20
no.2
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pp.412-424
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2019
In this study, the changes of the streamflow characteristics of the watershed were analysed depending on the infiltration methods of CAT. The study area, Boryeong-dam watershed located in Chungcheongnam-do area, has been suffered from severe drought in recent years and stabilized regarding on the storage rate through efforts such as constructing a channel connecting the upstream of Boryeong-dam from the downstream of the Geum river. In this study, the effects of soil infiltration parameters on the watershed streamflow characteristics were analyzed by the infiltration methods of CAT such as Rainfall Excess, Green&Ampt and Horton. And the parameter calibrations were conducted by SCEUA-P, a global optimization technique module of the PEST, the package for parameter optimization and uncertainty analysis, to compare the yearly variations of soil parameters for infiltration methods of CAT. In addition, the streamflow characteristics were analyzed for three infiltration methods by applying three different scenarios, such as applying calibrated parameters for every years to simulate the model for each years, applying calibrated parameters for the entire period to simulate the model for entire period, and applying the average value of yearly calibrated parameters to simulate the model for entire period.
Kim, Byoungkwan;Heo, Ye-Eun;Chon, Chul-Min;Lee, Sujeong
Resources Recycling
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v.27
no.6
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pp.59-67
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2018
Efflorescence is a white deposit of powders in the surface of cement concrete which can also occur in geopolymers. Efflorescence occurs when sodium ions in alkali activator react with atmospheric carbon dioxide to form sodium carbonate components. In this study, we investigated whether the secondary efflorescence can be reduced by controlling the Na/Al mole ratio or by changing the curing temperature and heat curing time in fly ash-based geopolymers. The 28 days compressive strength in geopolymers having Na/Al ratio of 1.0 was higher than geopolymers having Na/Al ratio of 0.8. The strength increased with the increasing curing temperature and longer heat curing time. On the other hand, efflorescence was lower when the curing temperature was high and the heat curing time was longer in the geopolymers having Na/Al ratio of 1.0. The geopolymers having Na/Al ratio of 0.8 showed accelerated efflorescence occurrence than the geopolymers having Na/Al ratio of 1.0. In order to reduce the occurrence of the secondary efflorescence of fly ash-based geopolymers, it will be advantageous to maintain the Na/Al ratio at 1.0, increase the curing temperature, and lengthen the heating curing time.
Kompsat-5 is the first Earth Observation Satellite which is equipped with an SAR in Korea. SAR images are generated by receiving signals reflected from an object by microwaves emitted from a SAR antenna. Because the wavelengths of microwaves are longer than the size of particles in the atmosphere, it can penetrate clouds and fog, and high-resolution images can be obtained without distinction between day and night. However, there is no color information in SAR images. To overcome these limitations of SAR images, colorization of SAR images using Cycle GAN, a deep learning model developed for domain translation, was conducted. Training of Cycle GAN is unstable due to the unsupervised learning based on unpaired dataset. Therefore, we proposed MS Cycle GAN applying multi-scale discriminator to solve the training instability of Cycle GAN and to improve the performance of colorization in this paper. To compare colorization performance of MS Cycle GAN and Cycle GAN, generated images by both models were compared qualitatively and quantitatively. Training Cycle GAN with multi-scale discriminator shows the losses of generators and discriminators are significantly reduced compared to the conventional Cycle GAN, and we identified that generated images by MS Cycle GAN are well-matched with the characteristics of regions such as leaves, rivers, and land.
Ahn, Myeonghui;Jang, Eun-kyung;Bae, Inhyeok;Ji, Un
KSCE Journal of Civil and Environmental Engineering Research
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v.40
no.6
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pp.571-581
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2020
Vegetation affects water level change and flow resistance in rivers and impacts waterway ecosystems as a whole. Therefore, it is important to have accurate information about the species, shape, and size of any river vegetation. However, it is not easy to collect full vegetation data on-site, so recent studies have attempted to obtain large amounts of vegetation data using terrestrial laser scanning (TLS). Also, due to the complex shape of vegetation, it is not easy to obtain accurate information about the canopy area, and there are limitations due to a complex range of variables. Therefore, the physical structure of vegetation was analyzed in this study by reconfiguring high-resolution point cloud data collected through 3-dimensional terrestrial laser scanning (3D TLS) in a voxel. Each physical structure was analyzed under three different conditions: a simple vegetation formation without leaves, a complete formation with leaves, and a patch-scale vegetation formation. In the raw data, the outlier and unnecessary data were filtered and removed by Statistical Outlier Removal (SOR), resulting in 17%, 26%, and 25% of data being removed, respectively. Also, vegetation volume by voxel size was reconfigured from post-processed point clouds and compared with vegetation volume; the analysis showed that the margin of error was 8%, 25%, and 63% for each condition, respectively. The larger the size of the target sample, the larger the error. The vegetation surface looked visually similar when resizing the voxel; however, the volume of the entire vegetation was susceptible to error.
In this study, the effects of solution components were investigated in the recovery of vanadium as ammonium metavanadate from vanadium-ore-salt roasting-water leaching solution. The vanadium-containing solution is strongly alkaline (pH 13), so the pH must be lowered to 9 or less to increase the ammonium metavanadate precipitation efficiency. However, in the process of adjusting the solution pH using sulfuric acid, aluminum ions are co-precipitated, which must be removed first. In this study, aluminum was precipitated in the form of an aluminum-silicate compound using sodium silicate, and the conditions for minimizing vanadium loss in this process were investigated. After aluminum removal, the silicate was precipitated and removed by adjusting the solution pH to 9 or less using sulfuric acid. In this process, the concentration and addition rate of sulfuric acid have a significant influence on the loss of vanadium, and vanadium loss was minimized as much as possible by slowly adding dilute sulfuric acid. Ammonium metavanadate was precipitated using three equivalents of ammonium chloride at room temperature from the aluminum-free, aqueous solution of vanadium following the pH adjustment process. The recovery yield of vanadium in the form of ammonium metavanadate exceeded 81%. After washing the product, vanadium pentoxide with 98.6% purity was obtained following heat treatment at 550 ℃ for 2 hours.
The use of segmented mirrors is one of the ways to make the primary mirror of a spaceborne satellite larger, where several small mirrors are combined into a large monolithic mirror. To align multiple segmented mirrors as one large mirror, there must be no discontinuity in the x, y-axis (tilt) and axial alignment error (piston) between adjacent mirrors. When the tilt and piston are removed, we can collect the light in one direction and get an expected clear image. Therefore, we need a precise wavefront sensor that can measure the alignment error of the segmented mirrors in nm scale. The tilt error can be easily detected by the point spread image of the segmented mirrors, while the piston error is hard to detect because of the absence of apparent features, but makes a downgraded image. In this paper we used an optical testing interferometer such as a Fizeau interferometer, which has various advantages when aligning the segmented mirror on the ground, and focused on measuring the axial displacement error of a segmented mirror as the basic research of measuring the piston errors between adjacent mirrors. First, we calculated the relationship between the axial displacement error of the segmented mirror and the surface defocus error of the interferometer and verified the calculated formula through experiments. Using the experimental results, we analyzed the measurement uncertainty and obtained the limitation of the Fizeau interferometer in detecting axial displacement errors.
Transactions of the Korean hydrogen and new energy society
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v.33
no.1
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pp.95-104
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2022
Micro hydropower is a readily available renewable energy source that can be harvested utilizing hydrokinetic turbines from shallow water canals, irrigation and industrial channel flows, and run-off river stream flows. These sources generally have low head (<1 m) and low velocity which makes it difficult to harvest energy using conventional turbines. A horizontal-axis screw turbine was designed and numerically tested to extract power from such low-head water sources. The 3-bladed screw-type turbine is placed horizontally perpendicular to the incoming flow, partially submerged in a narrow water channel at no-head condition. The turbine hydraulic performances were studied using Computational Fluid Dynamics models. Turbine design parameters such as the shroud diameter, the hub-to-shroud ratios, and the submerged depths were obtained through a steady-state parametric study. The resulting turbine configuration was then tested by solving the unsteady multiphase free-surface equations mimicking an actual open channel flow scenario. The turbine performance in the shallow channel were studied for various Tip Speed Ratios (TSR). The highest power coefficient was obtained at a TSR of 0.3. The turbine was then scaled-up to test its performance on a real site condition at a head of 0.3 m. The highest power coefficient obtained was 0.18. Several losses were observed in the 3-bladed turbine design and to minimize losses, the number of blades were increased to five. The power coefficient improved by 236% for a 5-bladed screw turbine. The fluid losses were minimized by increasing the blade surface area submerged in water. The turbine performance was increased by 74.4% after dipping the turbine to a bottom wall clearance of 30 cm from 60 cm. The final output of the novel horizontal-axis screw turbine showed a 2.83 kW power output at a power coefficient of 0.63. The turbine is expected to produce 18,744 kWh/year of electricity. The design feasibility test of the turbine showed promising results to harvest energy from small hydropower sources.
KSCE Journal of Civil and Environmental Engineering Research
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v.43
no.6
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pp.735-747
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2023
In recent times, the sharp increase in extreme flood damages due to climate change has posed a challenge to effectively address flood-related issues solely relying on conventional flood management infrastructure. In response to this problem, this study aims to consider the effectiveness of nature-based flood management approaches, specifically levee retreat and relocation. To achieve this, we utilized a 1D numerical model, HEC-RAS, to analyze the flood reduction effects concerning floodwater levels, flow velocities, and time-dependent responses to a 100-year frequency flood event. The analysis results revealed that the effect of creating a flood buffer zone of the nature-based solution extends from upstream to downstream, reducing flood water levels by up to 30 cm. The selection of the flow roughness coefficient in consideration of the nature-based flood buffer space creation characteristics should be based on precise criteria and scientific evidence because it is sensitive to the flood control effect analysis results. Notably, floodwater levels increased in some expanded floodplain sections, and the reduction in flow velocities varied depending on the ratio of the expanded cross-sectional area. In conclusion, levee retreat and floodplain expansion are viable nature-based alternatives for effective flood management. However, a comprehensive design approach is essential considering flood control effects, flow velocity reduction, and the timing of peak water levels. This study offers insights into addressing the challenges of climate-induced extreme flooding and advancing flood management strategies.
Journal of the Computational Structural Engineering Institute of Korea
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v.37
no.3
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pp.163-171
/
2024
Structural health monitoring for ships and offshore structures is important in various aspects. Ships and offshore structures are continuously exposed to various environmental conditions, such as waves, wind, and currents. In the event of an accident, immense economic losses, environmental pollution, and safety problems can occur, so it is necessary to detect structural damage or defects early. In this study, structural response data of multi-linked floating offshore structures under various wave load conditions was calculated by performing fluid-structure coupled analysis. Furthermore, the order reduction method with distortion base mode was applied to the structures for predicting the structural response by using the results of numerical analysis. The distortion base mode order reduction method can predict the structural response of a desired area with high accuracy, but prediction performance is affected by sensor arrangement. Optimization based on a genetic algorithm was performed to search for optimal sensor arrangement and improve the prediction performance of the distortion base mode-based reduced-order model. Consequently, a sensor arrangement that predicted the structural response with an error of about 84.0% less than the initial sensor arrangement was derived based on the root mean squared error, which is a prediction performance evaluation index. The computational cost was reduced by about 8 times compared to evaluating the prediction performance of reduced-order models for a total of 43,758 sensor arrangement combinations. and the expected performance was overturned to approximately 84.0% based on sensor placement, including the largest square root error.
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