• The Journal of Society for e-Business Studies
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• v.26 no.1
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• pp.67-78
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• 2021

The number of domestic e-commerce transactions has been breaking its own record by an annual average growth rate of over 20% based on volume for the past 5 years. Due to the rapid increase in e-commerce market, retail companies that have difficulty meeting consumers in person are in fierce competition to take the lead in the last mile service, which is the only point of contact with customers. Especially in the delivery area, where competition is most intense, the role of the fulfillment center is very important for service differentiation. It must be capable of fast product preparation ordered by consumers in accordance with the delivery service level. This study focuses on the order picking system for rapid order processing in the fulfillment center as an alternative for companies to gain competitive advantage in the e-commerce market. A mixed integer programming model was developed and implemented to optimize the stock replenishment in order picking facilities. The effectiveness was scientifically and objectively verified by simulation using the actual operation process and data.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.3
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• pp.147-155
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• 2022

The accumulated ice and snow during the operation of aircraft and railway vehicles can degrade aerodynamic performance or damage the major components of vehicles. Therefore, it is crucial to predict the temporal growth of ice for operational safety. Numerical simulation of ice is widely used owing to the fact that it is economically cheaper and free from similarity problems compared to experimental methods. However, numerical simulation of ice generally divides the analysis into multi-step and assumes the quasi-steady assumption that considers every time step as steady state. Although this method enables efficient analysis, it has a disadvantage in that it cannot track continuous ice evolution. The purpose of this study is to construct a surrogate model that can predict the temporal evolution of ice shape using reduced-order modeling. Reduced-order modeling technique was validated for various ice shape generated under 100 different icing conditions, and the effect of the number of training data and the icing conditions on the prediction error of model was analyzed.

• Structural Engineering and Mechanics
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• v.81 no.6
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• pp.665-675
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• 2022

The safety problems of giant hydraulic structures such as dams caused by terrorist attacks, earthquakes, and wars often have an important impact on a country's economy and people's livelihood. For the national defense department, timely and effective assessment of damage to or impending damage to dams and other structures is an important issue related to the safety of people's lives and property. In the field of damage assessment and vulnerability analysis, it is usually necessary to give the damage assessment results within a few minutes to determine the physical damage (crack length, crater size, etc.) and functional damage (decreased power generation capacity, dam stability descent, etc.), so that other defense and security departments can take corresponding measures to control potential other hazards. Although traditional numerical calculation methods can accurately calculate the crack length and crater size under certain combat conditions, it usually takes a long time and is not suitable for rapid damage assessment. In order to solve similar problems, this article combines simulation calculation methods with machine learning technology interdisciplinary. First, the common concrete gravity dam shape was selected as the simulation calculation object, and XFEM (Extended Finite Element Method) was used to simulate and calculate 19 cracks with different initial positions. Then, an LSTM (Long-Short Term Memory) machine learning model was established. 15 crack paths were selected as the training set and others were set for test. At last, the LSTM model was trained by the training set, and the prediction results on the crack path were compared with the test set. The results show that this method can be used to predict the crack propagation path rapidly and accurately. In general, this article explores the application of machine learning related technologies in the field of mechanics. It has broad application prospects in the fields of damage assessment and vulnerability analysis.

• Journal of the Korean Society for Geothermal and Hydrothermal Energy
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• v.18 no.4
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• pp.45-57
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• 2022

The Ministry of National Defense of the Republic of Korea is showing a lot of interest in net zero-energy buildings (NZEBs) to reduce energy consumption of military facilities and to promote green growth policy in military sector. The application of building passive technologies and renewable energies is essential to achieving NZEBs. This paper analyzed energy performance and energy cost on the conventional heating and cooling system (baseline scenario) and three different alternative scenarios (ALT 1, ALT 2 and ALT 3) applied in a hypothetical military building. A building modeling and simulation software (DesignBuilder V6.1) with EnergyPlus calculation engine was used to calculate the energy consumption for each scenario. Overall, when the GSHPs are applied to both space airconditioning and domestic hot water (DHW) production, Alt-2 and Alt-3, the amount of energy consumption for target building can be greatly reduced. In addition, when the building envelope performance is increased like Alt-3, the energy consumption can be further reduced. The annual energy cost analysis showed that the baseline was approximately 161 million KRW, while Alt-3 was approximately 33 million KRW. Therefore, it was analyzed that the initial construction cost increase could be recovered within about 6.7 years for ALT 3. The results of this study can help decision-makers to determine the optimal strategy for implementing GSHP systems in military buildings through energy performance and initial construction cost assessment.

• The Bulletin of The Korean Astronomical Society
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• v.46 no.2
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• pp.45.1-45.1
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• 2021

Horizon Run 5 (HR5) is a cosmological hydrodynamical simulation which captures the properties of the Universe on aGpc scale while achieving a resolution of 1kpc. This enormous dynamic range allows us to simultaneously capture the physics of the cosmic web on very large scales and account for the formation and evolution of dwarf galaxies on much smaller scales. On the back of a remarkable achievement of this, we have finished to run follow-up simulations which have 2 times larger volume than before and are expected to complementary to some limitations of previous HR simulations both for the study on the large scale features and the expansion history in a distant Universe. For these simulations, we consider the sub-grid physics of radiative heating/cooling, reionization, star formation, SN/AGN feedbacks, chemical evolution and the growth of super-massive blackholes. In order to do this project, we implemented a hybrid MPI-OpenMP version of the RAMSES code, 'RAMSES-OMP', which is specifically designed for modern many-core many thread parallel systems. These simulation successfully reproduce various observation result and provide a large amount of statistical samples of Lyman-alpha emitters and protoclusters which are important to understand the formation and expansion history of early universe. These are invaluable assets for the interpretation of current ΛCDM cosmology and current/upcoming deep surveys of the Universe, such as the world largest narrow band imaging survey, ODIN (One-hundred-square-degree Dark energy camera Imaging in Narrow band).

• International conference on construction engineering and project management
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• 2022.06a
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• pp.443-449
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• 2022

With climate change and the global population growth, the frequency and scope of wildfires are constantly increasing, which threatened people's lives and property. For example, according to California Department of Forestry and Fire Protection, in 2020, a total of 9,917 incidents related to wildfires were reported in California, with an estimated burned area of 4,257,863 acres, resulting in 33 fatalities and 10,488 structures damaged or destroyed. At the same time, the ongoing development of technology provides new tools to simulate and analyze the spread of wildfires. How to use new technology to reduce the losses caused by wildfire is an important research topic. A potentially feasible strategy is to simulate and analyze the spread of wildfires through computing technology to explore the impact of different factors (such as weather, terrain, etc.) on the spread of wildfires, figure out how to take preemptive/responsive measures to minimize potential losses caused by wildfires, and as a result achieve better management support of wildfires. In preparation for pursuing these goals, the authors used a powerful computing framework, Spark, developed by the Commonwealth Scientific and Industrial Research Organization (CSIRO), to study the effects of different weather factors (wind speed, wind direction, air temperature, and relative humidity) on the spread of wildfires. The test results showed that wind is a key factor in determining the spread of wildfires. A stable weather condition (stable wind and air conditions) is beneficial to limit the spread of wildfires. Joint consideration of weather factors and environmental obstacles can help limit the threat of wildfires.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.35 no.5
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• pp.95-101
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• 2023

Recent persistent coastal developments have expanded recreational areas and enhanced accessibility. However, this growth has also led to a rise in safety incidents. These accident factors can be divided into human-made and natural types. The latter is comprised of dynamic factors like waves, tides, sea fogs, and winds. While institutions like the Korea Meteorological Administration and the Korea Hydrographic and Oceanographic Agency already offer data on these dynamic factors, the resolution is often insufficient for a precise assessment of localized risks. In this study, to overcome these limitations, we utilized the dynamic information from existing open systems to construct a high-resolution numerical simulation. Through this, we developed an automated module to predict dynamic factors in localized coastal activity areas. Particularly during the module's construction, we compared and reviewed the numerical prediction results for waves with observed wave heights.

• Korean Journal of Materials Research
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• v.34 no.2
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• pp.111-115
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• 2024

Silicon carbide (SiC) has emerged as a promising material for next-generation power semiconductor materials, due to its high thermal conductivity and high critical electric field (~3 MV/cm) with a wide bandgap of 3.3 eV. This permits SiC devices to operate at lower on-resistance and higher breakdown voltage. However, to improve device performance, advanced research is still needed to reduce point defects in the SiC epitaxial layer. This work investigated the electrical characteristics and defect properties using DLTS analysis. Four deep level defects generated by the implantation process and during epitaxial layer growth were detected. Trap parameters such as energy level, capture-cross section, trap density were obtained from an Arrhenius plot. To investigate the impact of defects on the device, a 2D TCAD simulation was conducted using the same device structure, and the extracted defect parameters were added to confirm electrical characteristics. The degradation of device performance such as an increase in on-resistance by adding trap parameters was confirmed.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.4
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• pp.218-233
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• 2022

The long-term (1986~2020) predictability of the number of days of heat and cold damages for each growth stage of soybean is evaluated using the daily maximum and minimum temperature (Tmax and Tmin) data produced by Pusan National University Coupled General Circulation Model (PNU CGCM)-Weather Research and Forecasting (WRF). The Predictability evaluation methods for the number of days of damages are Normalized Standard Deviations (NSD), Root Mean Square Error (RMSE), Hit Rate (HR), and Heidke Skill Score (HSS). First, we verified the simulation performance of the Tmax and Tmin, which are the variables that define the heat and cold damages of soybean. As a result, although there are some differences depending on the month starting with initial conditions from January (01RUN) to May (05RUN), the result after a systematic bias correction by the Variance Scaling method is similar to the observation compared to the bias-uncorrected one. The simulation performance for correction Tmax and Tmin from March to October is overall high in the results (ENS) averaged by applying the Simple Composite Method (SCM) from 01RUN to 05RUN. In addition, the model well simulates the regional patterns and characteristics of the number of days of heat and cold damages by according to the growth stages of soybean, compared with observations. In ENS, HR and HSS for heat damage (cold damage) of soybean have ranged from 0.45~0.75, 0.02~0.10 (0.49~0.76, -0.04~0.11) during each growth stage. In conclusion, 01RUN~05RUN and ENS of PNU CGCM-WRF Chain have the reasonable performance to predict heat and cold damages for each growth stage of soybean in South Korea.

• Proceedings of the Korean Society of Crop Science Conference
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• 2017.06a
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• pp.8-9
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• 2017

Soybean yield has been low and unstable in Japan and other areas in East Asia, despite long history of cultivation. This is contrasting with consistent increase of yield in North and South America. This presentation tries to describe perspective of breaking stagnation of soybean yield in East Asia, considering the factors of the different yields between regions. Large amount of rainfall with occasional dry-spell in the summer is a nature of monsoon climate and as frequently stated excess water is the factor of low and unstable soybean yield. For example, there exists a great deal of field-to-field variation in yield of 'Tanbaguro' soybean, which is reputed for high market value and thus cultivated intensively and this results in low average yield. According to our field survey, a major portion of yield variation occurs in early growth period. Soybean production on drained paddy fields is also vulnerable to drought stress after flowering. An analysis at the above study site demonstrated a substantial field-to-field variation of canopy transpiration activity in the mid-summer, but the variation of pod-set was not as large as that of early growth. As frequently mentioned by the contest winners of good practice farming, avoidance of excess water problem in the early growth period is of greatest importance. A series of technological development took place in Japan in crop management for stable crop establishment and growth, that includes seed-bed preparation with ridge and/or chisel ploughing, adjustment of seed moisture content, seed treatment with mancozeb+metalaxyl and the water table control system, FOEAS. A unique success is seen in the tidal swamp area in South Sumatra with the Saturated Soil Culture (SSC), which is for managing acidity problem of pyrite soils. In 2016, an average yield of $2.4tha^{-1}$ was recorded for a 450 ha area with SSC (Ghulamahdi 2017, personal communication). This is a sort of raised bed culture and thus the moisture condition is kept markedly stable during growth period. For genetic control, too, many attempts are on-going for better emergence and plant growth after emergence under excess water. There seems to exist two aspects of excess water resistance, one related to phytophthora resistance and the other with better growth under excess water. The improvement for the latter is particularly challenging and genomic approach is expected to be effectively utilized. The crop model simulation would estimate/evaluate the impact of environmental and genetic factors. But comprehensive crop models for soybean are mainly for cultivations on upland fields and crop response to excess water is not fully accounted for. A soybean model for production on drained paddy fields under monsoon climate is demanded to coordinate technological development under changing climate. We recently recognized that the yield potential of recent US cultivars is greater than that of Japanese cultivars and this also may be responsible for different yield trends. Cultivar comparisons proved that higher yields are associated with greater biomass production specifically during early seed filling, in which high and well sustained activity of leaf gas exchange is related. In fact, the leaf stomatal conductance is considered to have been improved during last a couple of decades in the USA through selections for high yield in several crop species. It is suspected that priority to product quality of soybean as food crop, especially large seed size in Japan, did not allow efficient improvement of productivity. We also recently found a substantial variation of yielding performance under an environment of Indonesia among divergent cultivars from tropical and temperate regions through in a part biomass productivity. Gas exchange activity again seems to be involved. Unlike in North America where transpiration adjustment is considered necessary to avoid terminal drought, under the monsoon climate with wet summer plants with higher activity of gas exchange than current level might be advantageous. In order to explore higher or better-adjusted canopy function, the methodological development is demanded for canopy-level evaluation of transpiration activity. The stagnation of soybean yield would be broken through controlling variable water environment and breeding efforts to improve the quality-oriented cultivars for stable and high yield.