• Clean Technology
• /
• v.26 no.4
• /
• pp.293-303
• /
• 2020

According to the World Health Organization (WHO), air pollution is a typical health hazard, resulting in about 7 million premature deaths each year. Sulfur dioxide (SO2) is one of the major air pollutants, and the combustion process with sulfur-containing fuels generates it. Measuring SO2 generation in large combustion environments in real time and optimizing reduction facilities based on measured values are necessary to reduce the compound's presence. This paper describes the concentration measurement for SO2, a particulate matter precursor, using a wavelength modulation spectroscopy (WMS) of tunable diode laser absorption spectroscopy (TDLAS). This study employed a quantum cascade laser operating at 7.6 ㎛ as a light source. It demonstrated concentration measurement possibility using 64 multi-absorption lines between 7623.7 and 7626.0 nm. The experiments were conducted in a multi-pass cell with a total path length of 28 and 76 m at 1 atm, 296 K. The SO2 concentration was tested in two types: high concentration (1000 to 5000 ppm) and low concentration (10 ppm or less). Additionally, the effect of H2O interference in the atmosphere on the measurement of SO2 was confirmed by N2 purging the laser's path. The detection limit for SO2 was 3 ppm, and results were compared with the electronic chemical sensor and nondispersive infrared (NDIR) sensor.

• Journal of Digital Convergence
• /
• v.20 no.2
• /
• pp.203-215
• /
• 2022

The study is to investigate research trends and knowledge structures in the Smart Farm field. To achieve the research purpose, keywords and the relationship among keywords were analyzed targeting 104 Korean academic journals related to the Smart Farm in KCI(Korea Citation Index), and topics were analyzed using the LDA Topic Modeling technique. As a result of the analysis, the main keywords in the Korean Smart Farm-related research field were 'environment', 'system', 'use', 'technology', 'cultivation', etc. The results of Degree, Betweenness, and Eigenvector Centrality were presented. There were 7 topics, such as 'Introduction analysis of Smart Farm', 'Eco-friendly Smart Farm and economic efficiency of Smart Farm', 'Smart Farm platform design', 'Smart Farm production optimization', 'Smart Farm ecosystem', 'Smart Farm system implementation', and 'Government policy for Smart Farm' in the results of Topic Modeling. This study will be expected to serve as basic data for policy development necessary to advance Korean Smart Farm research in the future by examining research trends related to Korean Smart Farm.

• Composites Research
• /
• v.35 no.2
• /
• pp.115-119
• /
• 2022

The performance of carbon fiber is important for the production of these high-quality polymer composite materials such as CFRP (Carbon Fiber Reinforced Plastic). For this purpose, it is essential to use an optimized spinning process for improving the mechanical, physical, and structural properties of the precursor fiber, which greatly affects the properties of the carbon fiber, and the use of a suitable precursor polymer. In this study, the content of MAA (Methacrylic Acid), MAA injection time, and concentration of AIBN (2,2'-Azobis(2-methylpropionitrile)) were set as parameters for the polymer synthesis process, and Poly(AN-co-MAA) (poly(acrylonitrile-co-methacrylic acid)) was polymerized by solution polymerization. Poly(AN-co-MAA) with a molecular weight of 305,138 g/mol and an MAA ratio of 4.2% was dissolved in DMF (N,N-dimethylformamide) at a concentration of 16.0 wt%, and then a precursor fiber was prepared through dry-jet-wet spinning. The precursor fiber had a tensile strength of ~1.06 GPa and a tensile modulus of ~22.01 GPa, and no voids and structural defects were observed on the fiber.

• Journal of the Korean Institute of Gas
• /
• v.26 no.4
• /
• pp.41-57
• /
• 2022

The global demand for carbon neutrality in response to climate change is in a situation where it is necessary to prepare countermeasures for carbon trade barriers for some countries, including Korea, which is classified as an export-led economic structure and greenhouse gas exporter. Therefore, digital transformation, which is one of the predictable ways for the carbon-neutral transition model to be applied, should be introduced early. By applying digital technology to industrial gas manufacturing facilities used in one of the major industries, high-tech manufacturing industry, and hydrogen gas facilities, which are emerging as eco-friendly energy, abnormal detection, and diagnosis services are provided with cloud-based predictive diagnosis monitoring technology including operating knowledge. Here are the trends. Small and medium-sized companies that are in the blind spot of carbon-neutral implementation by confirming the direction of abnormal diagnosis predictive monitoring through optimization, augmented reality technology, IoT and AI knowledge inference, etc., rather than simply monitoring real-time facility status It can be seen that it is possible to disseminate technologies such as consensus knowledge in the engineering domain and predictive diagnostic monitoring that match the economic feasibility and efficiency of the technology. It is hoped that it will be used as a way to seek countermeasures against carbon emission trade barriers based on the highest level of ICT technology.

• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.35 no.6
• /
• pp.367-374
• /
• 2022

This papter presents the use of the automatic differential method based on the backpropagation method to obtain the design sensitivity and its application to topology optimization considering the stress constraints. Solving topology optimization problems with stress constraints is difficult owing to singularities, the local nature of stress constraints, and nonlinearity with respect to design variables. To solve the singularity problem, the stress relaxation technique is used, and p-norm for stress constraints is applied instead of local stresses for global stress measures. To overcome the nonlinearity of the design variables in stress constraint problems, it is important to analytically obtain the exact design sensitivity. In conventional topology optimization, design sensitivity is obtained efficiently and accurately using the adjoint variable method; however, obtaining the design sensitivity analytically and additionally solving the adjoint equation is difficult. To address this problem, the design sensitivity is obtained using a backpropagation technique that is used to determine optimal weights and biases in the artificial neural network, and it is applied to the topology optimization with the stress constraints. The backpropagation technique is used in automatic differentiation and can simplify the calculation of the design sensitivity for the objectives or constraint functions without complicated analytical derivations. In addition, the backpropagation process is more computationally efficient than solving adjoint equations in sensitivity calculations.

• Journal of Korea Water Resources Association
• /
• v.55 no.spc1
• /
• pp.1211-1222
• /
• 2022

Abnormal condition inevitably occurs during operation of water distribution system (WDS) and requires the isolation of certain areas using isolation valves. In general, the determination of the optimal location of isolation valves considered minimization of hydraulic failures as isolation of certain areas causes a change in hydraulic states (e.g., flow direction, velocity, pressure, etc.). Water quality failure can also be induced by changes in hydraulics, which have not been considered for isolation valve system design. Therefore, this study proposes a new isolation valve system design methodology to prevent unexpected water quality failure events. The new methodology considers flow direction change ratio (FDCR), which accounts for flow direction changes after isolation of the area, as a constraint while reliability is used as the objective function. The optimal design model has been applied to a synthetic grid network and the results are compared with the traditional design approach. Results show that considering FDCR can eliminate flow direction changes while average pressure and coefficient of variation of pressure, velocity, and hydraulic geodesic index (HGI) outperform compared to the traditional design approach. The proposed methodology is expected to be a useful approach to minimizing unexpected consequences by traditional design approaches.

• The Journal of the Convergence on Culture Technology
• /
• v.9 no.3
• /
• pp.861-866
• /
• 2023

Unlike conventional smart farms that require chemical fertilizers and large spaces, aquaponics farming, which utilizes the symbiotic relationship between aquatic organisms and crops to grow crops even in abnormal environments such as environmental pollution and climate change, is being actively researched. Different crops require different environments and nutrients for growth, so it is necessary to configure the ratio of aquatic organisms optimized for crop growth. This study proposes a method to measure the degree of growth based on area and volume using image processing techniques in an aquaponics environment. Tilapia, carp, catfish, and lettuce crops, which are aquatic organisms that produce organic matter through excrement, were tested in an aquaponics environment. Through 2D and 3D image analysis of lettuce and real-time data analysis, the growth degree was evaluated using the area and volume information of lettuce. The results of the experiment proved that it is possible to manage cultivation by utilizing the area and volume information of lettuce. It is expected that it will be possible to provide production prediction services to farmers by utilizing aquatic life and growth information. It will also be a starting point for solving problems in the changing agricultural environment.

• Journal of the Microelectronics and Packaging Society
• /
• v.31 no.2
• /
• pp.63-68
• /
• 2024

With the increasing use of transparent displays and flexible devices, polymer substrates offering excellent flexibility and strength are in demand. Since polymers are sensitive to heat, precise temperature control during the process is necessary. The study proposes a temperature measurement system for the laser processing area within the polymer base, aiming to address the drawbacks of using these polymer bases in laser-based selective processing technology. It presents the possibility of optimizing the process conditions of the polymer substrate through local temperature change measurements in the laser processing area. We developed and implemented the PDPT (Photodiode-based Planck Thermometry) to measure temperature in the laser-processing area. PDPT is a non-destructive, contact-free system capable of real-time measurement of local temperature increases. We monitored the temperature fluctuations during the laser processing of the polymer substrate. The study shows that the proposed laser-based temperature measurement technology can measure real-time temperature during laser processing, facilitating optimal production conditions. Furthermore, we anticipate the application of this technology in various laser-based processes, including essential micro-laser processing and 3D printing.

• Geophysics and Geophysical Exploration
• /
• v.27 no.3
• /
• pp.159-170
• /
• 2024

The bioreactor method, in which leachate is reinjected into a landfill for rapid decomposition and stabilization of buried waste, is being applied and tested at many landfills because of its numerous advantages. To apply the bioreactor method to a landfill successfully, it is very important to understand the behavioral characteristics of the injected leachate. In this study, electrical resistivity monitoring was performed to estimate the behavior of a landfill leachate in Korea where the bioreactor method was applied. For the electrical resistivity monitoring, a baseline survey was conducted in August 2013 before the leachate was injected, and time-lapse monitoring surveys were conducted four times after injection. The electrical resistivity monitoring results revealed reductions in electrical resistivity in the landfill attributable to the injected leachate, and the change in its characteristics over time was confirmed. In addition, by newly defining the electrical resistivity change ratio and applying it in this study, the spatial distribution and behavior of the leachate over time were effectively identified. More research on optimization of data acquisition and integrated monitoring methods using various techniques should be conducted in the near future.

• Journal of the Korean earth science society
• /
• v.37 no.7
• /
• pp.448-464
• /
• 2016

The purpose of this study is to optimize the parameters related to consensus coherency within the PCL 1300, the operating program of wind profiler, from a validation of wind data between rawinsonde and wind profiler at Chupungryeong ($36^{\circ}13^{\prime}$, $127^{\circ}59^{\prime}$) site in Korea. It is then to analyze the diurnal and seasonal characteristics of the turbulence energy dissipation rate (${\varepsilon}$) in clear and rainy days from March 2009 to February 2010. In comparison of the wind data between wind profiler and rawinsonde during April 22-23, 2010, it was shown in a big error more than $10ms^{-1}$ over the height of 3,000 meters in the zonal (u) and meridional (v) wind components. When removing more than $10ms^{-1}$ in each wind speed difference of u an v components between the two instruments, the correlation coefficients of these wind components were 0.92 and 0.88, respectively, and the root mean square errors were 3.07 and $1.06ms^{-1}$. Based on these results, when the data processing time and the minimum available data within the PCL 1300 program were adjusted as 30 minutes and 60%, respectively, the bias errors were small. In addition, as a result of an analysis of sensitivity to consensus coherency of u and v components within the PCL1300 program, u components were underestimated in radial coherency, instantaneous and winbarbs coherency, whereas v components were overestimated. Finally by optimizing parameters of the PCL1300 program, the diurnal and seasonal means of ${\varepsilon}$ at each height were higher in rainy days than those in clear days because of increasing in the vertical wind speed due to upward and downward motions. The mean ${\varepsilon}$ for clear and rainy days in winter was lower than those of other seasons, due to stronger horizontal wind speed in winter than those in other seasons. Consequently, when the turbulence energy dissipation rates in the vertical wind speed of more than ${\pm}10cm\;s^{-1}$ were excluded for clear and rainy days, the mean ${\varepsilon}$ in rainy days was 6-7 times higher than that in clear days, but when considering them, it was 4-5 times higher.