• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.172-172
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• 2020

In recent years, soil erosion has come to be regarded as an essential environmental problem in human life. Soil erosion causes various on- and off-site problems such as ecosystem destruction, decreased agricultural productivity, increased riverbed deposition, and deterioration of water quality in streams. To solve these problems caused by soil erosion, it is necessary to quantify where, when, how much soil erosion occurs. Empirical erosion models such as the Universal Soil Loss Equation (USLE) family models have been widely used to make spatially distributed soil erosion vulnerability maps. Even if the models detect vulnerable sites relatively well by utilizing big data related to climate, geography, geology, land use, etc. within study domains, they do not adequately describe the physical process of soil erosion on the ground surface caused by rainfall or overland flow. In other words, such models remain powerful tools to distinguish erosion-prone areas at the macro scale but physics-based models are necessary to better analyze soil erosion and deposition and eroded particle transport. In this study, the physics-based Surface Soil Erosion Model (SSEM) was upgraded based on field survey information to produce sediment yield at the watershed scale. The modified model (hereafter MoSE) adopted new algorithms on rainfall kinematic energy and surface flow transport capacity to simulate soil erosion more reliably. For model validation, we applied the model to the Doam dam watershed in Gangwon-do and compared the simulation results with the USLE outputs. The results showed that the revised physics-based soil erosion model provided more improved and reliable simulation results than the USLE in terms of the spatial distribution of soil erosion and deposition.

• Journal of KIISE:Information Networking
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• v.37 no.3
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• pp.167-174
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• 2010

Recently the distributed topology control algorithm for constructing the Recrystallization Topology in the unstructured peer-to-peer network was proposed. In this paper, we prove that such a hierarchical topology is a scale-free power-law network. We present a model of a construction process of the distributed protocol, and analyze it based on a mean-field approximation and the continuum theory, so that we show that the constructed Recrystallization Topology is a scale-free network. In the proposed model, all nodes are born with some initial attractiveness and the system incorporates the rewiring of some links at every time step. Some old links are removed with the anti-preferential probability, and some new links are added with preferential probability. In other words, according to the distributed algorithm, each node makes connections to the more-preferential nodes having higher hit-ratio than other nodes, while it disconnects the anti-preferential nodes having lesser hit-ratio. This gives a realistic description of the local processes forming the recrystallization topology in unstructured peer-to-peer network. We calculate analytically the degree distribution. The analytic result indicates that the constructed network is a scale-free network, of which the scaling exponent is 3.

• Journal of Biosystems Engineering
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• v.33 no.5
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• pp.362-369
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• 2008

There is developing interest in precision agriculture in Korea, despite the fact that typical Korean fields are less than 1 ha in size. Describing within-field variability in typical Korean production settings is a fundamental first step toward determining the size of management zones and the inter-relationships between limiting factors, for establishment of site-specific management strategies. Measurements of rice (Oriza Sativa L) yield, chlorophyll content, and soil properties were obtained in a small (100-m by 30-m) Korean rice paddy field. Yield data were manually collected on 10-m by 5-m grids (180 samples with 3 samples in each of 60 grid cells) and chlorophyll content was measured using a Minolta SPAD 502 in 2-m by 2-m grids. Soil samples were collected at 275 points to compare results from sampling at different scales. Ten soil properties important for rice production in Korea were determined through laboratory analyses. Variogram analysis and point kriging with and without median polishing were conducted to determine the variability of the measured parameters. Influence of variogram model selection and other parameters on the interpretation of the data was investigated. For many of the data, maximum values were greater than double the minimum values, indicating considerable spatial variability in the small paddy field, and large-scale spatial trends were present. When variograms were fit to the original data, the limits of spatial dependency for rice yield and SP AD reading were 11.5 m and 6.5 m, respectively, and after detrending the limits were reduced to 7.4 m and 3.9 m. The range of spatial dependency for soil properties was variable, with several having ranges as short as 2 m and others having ranges greater than 30 m. Kriged maps of the variables clearly showed the presence of both large-scale (trend) variability and small-scale variability in this small field where it would be reasonable to expect uniformity. These findings indicate the potential for applying the principles and technology of precision agriculture for Korean paddy fields. Additional research is needed to confirm the results with data from other fields and crops.d similar tendency with the result for the frequency less than 20 Hz, but the width of change was reduced highly.

• Wind and Structures
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• v.16 no.4
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• pp.301-322
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• 2013

Recent major post-hurricane damage assessments in the United States have reported that the most common damages result from the loss of building roof coverings and subsequent wind driven rain intrusion. In an effort to look further into this problem, this paper presents a full-scale (Wall of Wind --WoW--) investigation of external and underneath wind pressures on roof tiles installed on a low-rise building model with various gable roofs. The optimal dimensions for the low-rise building that was tested with the WOW are 2.74 m (9 ft) long, 2.13 m (7 ft) wide, and 2.13 m (7 ft) high. The building is tested with interchangeable gable roofs at three different slopes (2:12; 5:12 and 7:12). The field tiles of these gable roofs are considered with three different tile profiles namely high (HP), medium (MP), and low profiles (LP) in accordance with Florida practice. For the ridge, two different types namely rounded and three-sided tiles were considered. The effect of weather block on the "underneath" pressure that develops between the tiles and the roof deck was also examined. These tests revealed the following: high pressure coefficients for the ridge tile compared to the field tiles, including those located at the corners; considerably higher pressure on the gable end ridge tiles compared to ridge tiles at the middle of the ridge line; and marginally higher pressure on barrel type tiles compared to the three-sided ridge tiles. The weather blocking of clay tiles, while useful in preventing water intrusion, it doesn't have significant effect on the wind loads of the field tiles. The case with weather blocking produces positive mean underneath pressure on the field tiles on the windward side thus reducing the net pressures on the windward surface of the roof. On the leeward side, reductions in net pressure to a non-significant level were observed due to the opposite direction of the internal and external pressures. The effect of the weather blocking on the external pressure on the ridge tile was negligible.

• Journal of Ocean Engineering and Technology
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• v.35 no.1
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• pp.75-81
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• 2021

Artificial Coral Reefs (ACRs) have been introduced to help solve coastal erosion problems, but their feasibility has not been assessed with field data. This study conducted a feasibility analysis of ACRs on their erosion mitigation effects by performing a case study of Cheonjin-Bongpo beach, South Korea. A numerical-physical combined analysis was carried out using a SWAN model simulation and physical model test with a scale of 1/25 based on field observations of Cheonjin-Bongpo beach. Both Dean's parameter and the surf-scaling parameter were applied to comparative analysis between the absence and presence conditions of the ACR. The results for this combined method indicate that ACR attenuates the wave height significantly (59~71%). Furthermore, ACR helps decrease the mass flux (~50%), undertow (~80%), and maximum wave set up (~61%). The decreases in Dean's parameter (~66%) and the surf-scaling parameter suggest that the wave properties changed from the dissipative type to the reflective type even under high wave conditions. Consequently, an ACR can enhance shoreline stability.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.6
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• pp.41-55
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• 2023

In order to secure sustainable competitiveness of startups, business model innovation is an important task to achieve competitive advantage by transforming the various elements that make up the business model. This study conducted a multi-case analysis study on leading smart farm companies around the world using an analysis framework based on business model theory. Through this, we sought to identify business model types and their constituent elements. For this, 19 companies were selected from the list of top 10 investment startups of the year for the past three years published by Agfunder, a global investment research company specializing in AgTech. Then data collection and analysis of the company cases were conducted according to the case study protocol. As a result of the study, the business model types were analyzed into four types: large-scale centralized production model, medium-to-large local distributed production model, small-scale hyperlocal modular FaaS model, and small-scale hyperlocal turnkey solution supply model. A comparative analysis was conducted on five business model components for each type, and strategic implications were derived through this. This study is expected to contribute to improving the competitiveness of domestic smart farm startups and diversifying their strategies by identifying the business models of overseas leading companies in the smart farm field using an academic analysis framework.

• Smart Structures and Systems
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• v.21 no.5
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• pp.591-600
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• 2018

The probabilistic characterization of wind field characteristics is a significant task for fatigue reliability assessment of long-span railway bridges in wind-prone regions. In consideration of the effect of wind direction, the stochastic properties of wind field should be represented by a bivariate statistical model of wind speed and direction. This paper presents the construction of the bivariate model of wind speed and direction at the site of a railway arch bridge by use of the long-term structural health monitoring (SHM) data. The wind characteristics are derived by analyzing the real-time wind monitoring data, such as the mean wind speed and direction, turbulence intensity, turbulence integral scale, and power spectral density. A sequential quadratic programming (SQP) algorithm-based finite mixture modeling method is proposed to formulate the joint distribution model of wind speed and direction. For the probability density function (PDF) of wind speed, a double-parameter Weibull distribution function is utilized, and a von Mises distribution function is applied to represent the PDF of wind direction. The SQP algorithm with multi-start points is used to estimate the parameters in the bivariate model, namely Weibull-von Mises mixture model. One-year wind monitoring data are selected to validate the effectiveness of the proposed modeling method. The optimal model is jointly evaluated by the Bayesian information criterion (BIC) and coefficient of determination, $R^2$. The obtained results indicate that the proposed SQP algorithm-based finite mixture modeling method can effectively establish the bivariate model of wind speed and direction. The established bivariate model of wind speed and direction will facilitate the wind-induced fatigue reliability assessment of long-span bridges.

• Korean Chemical Engineering Research
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• v.46 no.5
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• pp.922-930
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• 2008

The selective non-catalytic reduction(SNCR) performance is sensitive to the process parameters such as flow velocity, reaction temperature and mixing of reagent(ammonia or urea) with the flue gases. Therefore, the knowledge of the velocity field, temperature field and species concentration distribution is crucial for the design and operation of an effective SNCR injection system. In this work, a full-scale two-dimensional computational fluid dynamics(CFD)-based reacting model involving a droplet model is built and validated with the data obtained from a pilot-scale urea-based SNCR reactor installed with a 150 kW LPG burner. The kinetic mechanism with seven reactions for nitrogen oxides($NO_x$) reduction by urea-water solution is used to predict $NO_x$ reduction and ammonia slip. Using the turbulent reacting flow CFD model involving the discrete droplet phase, the CFD simulation results show maximum 20% difference from the experimental data for NO reduction. For $NH_3$ slip, the simulation results have a similar tendency with the experimental data with regard to the temperature and the normalized stoichiometric ratio(NSR).

• Journal of the Korean Geotechnical Society
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• v.31 no.1
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• pp.15-24
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• 2015

This paper presents the results of a reduced-scale physical model investigation into the effect of drilling fluid with different mix designs for bore hole collapse prevention. The bore hole collapse prevention mechanism for the bentonite based drilling fluid was first discussed together with the effect of conditioning with different additives on engineering characteristics of bentonite based drilling fluid. Reduced-scale model tests were then carried out considering field procedures for cases with a decomposed granitic soil with 20% fines and a sand with various drilling fluids with different mix designs. The results indicated that the addition of polymer to the bentonite based drilling fluid decreases the amount of drilling fluid injected, the drilling fluid infiltration thickness and increases the final depth of excavation. Also revealed is that the effect of polymer on the performance of drilling fluid is more pronounced in the decomposed granite soil with 20% fines than the sand. Practical implications of the findings from this study are discussed in great detail.

• Proceedings of the KSME Conference
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• 2001.06e
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• pp.386-391
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• 2001

A finite element code based on P2P1 tetra element has been developed for the large eddy simulation (LES) of turbulent flows around a complex geometry. Fractional 4-step algorithm is employed to obtain time accurate solution since it is less expensive than the integrated formulation, in which the velocity and pressure fields are solved at the same time. Crank-Nicolson method is used for second order temporal discretization and Galerkin method is adopted for spatial discretization. For very high Reynolds number flows, which would require a formidable number of nodes to resolve the flow field, SUPG (Streamline Upwind Petrov-Galerkin) method is applied to the quadratic interpolation function for velocity variables, Noting that the calculation of intrinsic time scale is very complicated when using SUPG for quadratic tetra element of velocity variables, the present study uses a unique intrinsic time scale proposed by Codina et al. since it makes the present three-dimensional unstructured code much simpler in terms of implementing SUPG. In order to see the effect of numerical diffusion caused by using an upwind scheme (SUPG), those obtained from P2P1 Galerkin method and P2P1 Petrov-Galerkin approach are compared for the flow around a sphere at some Reynolds number. Smagorinsky model is adopted as subgrid scale models in the context of P2P1 finite element method. As a benchmark problem for code validation, turbulent flows around a sphere and a MIRA model have been studied at various Reynolds numbers.