• Journal of the Korean Society of Hazard Mitigation
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• v.10 no.2
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• pp.23-30
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• 2010

The research presents moisture content measuring and calibration method of road pavement, especially asphalt concrete pavement for performance evaluation or remaining life prediction using Time Domain Reflectometry(TDR) sensor, CS616 made by campbell INC. Before calibration test of CS616, accomplished a sensor verification tests. Verification test items were covering depth and interference effect of two CS616 sensors, temperature effects between $5^{\circ}C\sim25^{\circ}C$ and compaction ratio effects. Covering depth and interference effects between two CS616 sensors were just small and the effects of temperature and compaction ratio effected a Volumetric Moisture Contents at $\pm6%$ under disregard appeared with the fact that was possible. Also, obtained the calibration equation of the subgrade and subbase course, $R^2$ showed above of all 0.9.

• Asian Journal of Atmospheric Environment
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• v.2 no.2
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• pp.116-124
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• 2008

In this study, the Tier 2 method recommended by the Intergovernmental Panel on Climate Change (IPCC) was used to predict the methane generation rate at two landfill sites, designated as Y and C for purposes of this study, in South Korea. Factors such as the average annual waste disposal, methane emissions ($L_0$) and methane gas generation rate constant (k) were estimated by analyses of waste and the historical data for the landfills. The value of k was estimated by field experiments and then the changes in the methane generation rate were predicted through the year 2050, based on the value of k. The Y landfill site, which was in operation until the year 2008, will generate a total of 17, 198.7 tons by the end of 2018, according to our estimations. At the C landfill site, which will not be closed until the end of 2011, the amount of methane gas generated in 2011 will be 3,316 tons and the total amount of gas generated by 2029 will be 61,200 tons. The total production rate of methane gas at the C landfill is higher than that of the Y landfill. This indicates that the capacity of a landfill site affects the production rate of methane gas. However, the interrelation between the generation rate of methane and the value of k is weak. In addition, the generation of methane gas does not cease even when the operations at a landfill site come to a close and the methane gas production rate is at its highest at end of the operating life of a landfill site.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.1
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• pp.1-6
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• 2013

Three Surface cracks are among the more common flaws in aircraft and pressure vessel components. Accurate stress intensity analyses and crack growth rate data of surface-cracked components are needed for reliable prediction of their fatigue life and fracture strengths. Three Dimensional finite element method (FEM) was used to obtain the stress intensity factor for surface cracks existing in structures. A geometry model, i.e. a solid containing one or several 3D cracks is defined. Nodes are generated by bucket method, and quadratic tetrahedral solid elements are generated by the Delaunay triangulation techniques. To examine accuracy and efficiency of the present system, the stress intensity factor for a semi-elliptical surface crack in cylindrical structures subjected to pressure is calculated. Analysis results by present system showed good agreement with those by ASME equation and Raju-Newman's equation.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.2
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• pp.200-209
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• 2019

When forecasting future values, a model estimated after minimizing training errors can yield test errors higher than the training errors. This result is the over-fitting problem caused by an increase in model complexity when the model is focused only on a given dataset. Some regularization and resampling methods have been introduced to reduce test errors by alleviating this problem but have been designed for use with only a given dataset. In this paper, we propose a new optimization approach to reduce test errors by transforming a test error minimization problem into a training error minimization problem. To carry out this transformation, we needed additional data for the given dataset, termed pseudo data. To make proper use of pseudo data, we used three types of missing data imputation techniques. As an optimization tool, we chose the least squares method and combined it with an extra pseudo data instance. Furthermore, we present the numerical results supporting our proposed approach, which resulted in less test errors than the ordinary least squares method.

• Journal of Korean Medical classics
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• v.32 no.2
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• pp.17-31
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• 2019

Objectives : Understanding the Ten Stems and Twelve Branches is necessary to grasp the laws of change in Heaven and Earth. Methods : Based on relevant contents in East Asian classics, the Yin Yang, Sibling Wuxing, Husband-Wife Wuxing combinations as well as Mutual Collision and Zangfu combination were examined. Results & Conclusion : Yin Yang combination of the Ten Stems are divided according to odd/evenness. The Sibling Wuxing combination is categorized according to one life cycle of vegetation, resulting in Jia Yi Wood, Bing Ding Fire, Wu Ji Earth, Geng Xin Metal, Ren Gui Water. The Husband-Wife Wuxing combination of the Ten Stems are Jia Ji Earth, Yi Geng Metal, Bing Xin Water, Ding Ren Wood, Wu Gui Fire, which corresponds to the principles of the Duihuazuoyong Theory. Within the Husband-Wife Wuxing combination lies three principles which are Yin Yang combination, Mutual Restraining combination, and the Yang Stem restraining the Yin Stem. The Mutual Collision of the Ten Stems are Jia and Geng, Yi and Xin, Ren and Bing, Gui and Ding against each other. In matching Zangfu to the Ten Stems, Jia matches with Gallbladder, Yi matches with Liver; Bing matches with Small Intestine, Ding matches with Heart; Wu matches with Stomach, Ji matches with Spleen; Geng matches with Large Intestine, Xin matches with Lung; Ren matches with Bladder, Gui matches with Kidney. : When the adjacent vectors are extracted, the count-based word embedding method derives the main herbs that are frequently used in conjunction with each other. On the other hand, in the prediction-based word embedding method, the synonyms of the herbs were derived.

• Steel and Composite Structures
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• v.46 no.3
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• pp.385-401
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• 2023

Steel is becoming increasingly popular due to its high strength, excellent ductility, great assembly performance, and recyclability. In reality, steel structures serving for a long time in atmospheric, industrial, and marine environments inevitably suffer from corrosion, which significantly decreases the durability and the service life with the exposure time. For the mechanical properties of corroded steel, experimental studies are mainly conducted. The existing numerical analyses only evaluate the mechanical properties based on corroded morphology at the isolated time-in-point, ignoring that this morphology varies continuously with corrosion time. To solve this problem, the relationships between pit depth expectation, standard deviation, and corrosion time are initially constructed based on a large amount of wet-dry cyclic accelerated test data. Successively, based on that, an in-situ pitting evolution method for evaluating the residual tensile strength of corroded steel is proposed. To verify the method, 20 repeated simulations of mass loss rates and mechanical properties are adopted against the test results. Then, numerical analyses are conducted on 135 models of corrosion pits with different aspect ratios and uneven corrosion degree on two corroded surfaces. Results show that the power function with exponents of 1.483 and 1.091 can well describe the increase in pit depth expectation and standard deviation with corrosion time, respectively. The effect of the commonly used pit aspect ratios of 0.10-0.25 on yield strength and ultimate strength is negligible. Besides, pit number ratio α equating to 0.6 is the critical value for the strength degradation. When α is less than 0.6, the pit number increases with α, accelerating the degradation of strength. Otherwise, the strength degradation is weakened. In addition, a power function model is adopted to characterize the degradation of yield strength and ultimate strength with corrosion time, which is revised by initial steel plate thickness.

• Korean Journal of Agricultural and Forest Meteorology
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• v.18 no.1
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• pp.55-63
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• 2016

Temperature lapse rate within the planetary boundary layer shows a diurnal cycle with a substantial variation. The widely-used lapse rate value for the standard atmosphere may result in unaffordable errors if used in interpolating hourly temperature in complex terrain. We propose a simple method for estimating hourly lapse rate and evaluate whether this scheme is better than the conventional method using the standard lapse rate. A standard curve for lapse rate based on the diurnal course of temperature was drawn using upper air temperature for 1000hPa and 925hPa standard pressure levels. It was modulated by the hourly sky condition (amount of clouds). In order to test the reliability of this method, hourly lapse rates for the 500-600m layer over Daegwallyeong site were estimated by this method and compared with the measured values by an ultrasonic temperature profiler. Results showed the mean error $-0.0001^{\circ}C/m$ and the root mean square error $0.0024^{\circ}C/m$ for this vertical profile experiment. An additional experiment was carried out to test if this method is applicable for the mountain slope lapse rate. Hourly lapse rates for the 313-401m slope range in a complex watershed ('Hadong Watermark 2') were estimated by this method and compared with the observations. We found this method useful in describing diurnal cycle and variation of the mountain slope lapse rate over a complex terrain despite larger error compared with the vertical profile experiment.

• Korean Journal of Food Science and Technology
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• v.20 no.1
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• pp.6-12
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• 1988

To improve the individual packaging method and extend the shelf life of mackerel (Scomber japonicus), salted and unsalted mackerel fillets were packaged in laminated plastic film bag (Nylon/PE: $20{\mu}m/40{\mu}m,\;12{\times}15$ cm) filled with $CO_2$ gas, in vacuum, and stored at O and/or $5^{\circ}C$. The other samples were packaged in plastic foam trays, overwrapped with oxygen permeable film (control), and stored at same temperature. Volatile basic nitrogen (VBN), trimethylamine (TMA), histamine (HM) and viable cell counts (VCC) were progressed with the increasing of storage time, but thiobarbituric acid (TBA) values decreased gradually after reaching at a maximum peak in 5-9 days. Judging from 4 chemical components, VBN was the most available component in quality judgement of mackerel fillets and its upper limiting content was 25 mg%. Regression equation for shelf life prediction of mackerel fillets with sensory evaluation and VBN component was determined.

• Korean Journal of Agricultural and Forest Meteorology
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• v.18 no.4
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• pp.298-306
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• 2016

Planting date shift is one of the means of adapting to climate change in Kimchi Cabbage growers in major production areas in Korea. This study suggests a method to estimate the potential yield of Kimchi Cabbage based on daily temperature accumulation during the growth period from planting to maturity which is determined by a plant phenology model tuned to Kimchi Cabbage. The phenology model converts any changes in the thermal condition caused by the planting date shift into the heat unit accumulation during the growth period, which can be calculated from daily temperatures. The physiological maturity is estimated by applying this model to a variable development rate function depending either on growth or heading stage. The cabbage yield prediction model (Ahn et al., 2014) calculates the potential yield of summer cabbage by accumulating daily heat units for the growth period. We combined these two models and applied to the 1km resolution climate scenario (2000-2100) based on RCP8.5 for South Korea. Potential yields in the current normal year (2001-2010) and the future normal year (2011-2040, 2041-2070, and 2071-2100) were estimated for each grid cell with the planting dates of July 1, August 1, September 1, and October 1. Based on the results, we divided the whole South Korea into 810 watersheds, and devised a three - dimensional evaluation chart of the time - space - yield that enables the user to easily find the optimal planting date for a given watershed. This method is expected to be useful not only for exploring future new cultivation sites but also for developing cropping systems capable of adaptation to climate change without changing varieties in existing production areas.

• Journal of Bio-Environment Control
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• v.31 no.3
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• pp.152-162
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• 2022

This study developed simulation model for predicting the greenhouse interior environment using artificial intelligence machine learning techniques. Various methods have been studied to predict the internal environment of the greenhouse system. But the traditional simulation analysis method has a problem of low precision due to extraneous variables. In order to solve this problem, we developed a model for predicting the temperature inside the greenhouse using machine learning. Machine learning models are developed through data collection, characteristic analysis, and learning, and the accuracy of the model varies greatly depending on parameters and learning methods. Therefore, an optimal model derivation method according to data characteristics is required. As a result of the model development, the model accuracy increased as the parameters of the hidden unit increased. Optimal model was derived from the GRU algorithm and hidden unit 6 (r² = 0.9848 and RMSE = 0.5857℃). Through this study, it was confirmed that it is possible to develop a predictive model for the temperature inside the greenhouse using data outside the greenhouse. In addition, it was confirmed that application and comparative analysis were necessary for various greenhouse data. It is necessary that research for development environmental control system by improving the developed model to the forecasting stage.