• Journal of Korean Society of Environmental Engineers
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• v.32 no.2
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• pp.165-174
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• 2010

The numerical modeling of a coal gasification reaction occurring in an entrained flow coal gasifier is presented in this study. The purposes of this study are to develop a reliable evaluation method of coal gasifier not only for the basic design but also further system operation optimization using a CFD(Computational Fluid Dynamics) method. The coal gasification reaction consists of a series of reaction processes such as water evaporation, coal devolatilization, heterogeneous char reactions, and coal-off gaseous reaction in two-phase, turbulent and radiation participating media. Both numerical and experimental studies are made for the 1.0 ton/day entrained flow coal gasifier installed in the Korea Institute of Energy Research (KIER). The comprehensive computer program in this study is made basically using commercial CFD program by implementing several subroutines necessary for gasification process, which include Eddy-Breakup model together with the harmonic mean approach for turbulent reaction. Further Lagrangian approach in particle trajectory is adopted with the consideration of turbulent effect caused by the non-linearity of drag force, etc. The program developed is successfully evaluated against experimental data such as profiles of temperature and gaseous species concentration together with the cold gas efficiency. Further intensive investigation has been made in terms of the size distribution of pulverized coal particle, the slurry concentration, and the design parameters of gasifier. These parameters considered in this study are compared and evaluated each other through the calculated syngas production rate and cold gas efficiency, appearing to directly affect gasification performance. Considering the complexity of entrained coal gasification, even if the results of this study looks physically reasonable and consistent in parametric study, more efforts of elaborating modeling together with the systematic evaluation against experimental data are necessary for the development of an reliable design tool using CFD method.

• International Journal of Highway Engineering
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• v.11 no.4
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• pp.69-78
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• 2009

Korea has achieved significant economic growth with building the Gyeongbu Expressway. As the number of new road construction projects has decreased, it becomes more important to maintain optimal status of the current road networks. One of the best ways to accomplish it is weight enforcement as active control measure of traffic load. This study is to develop High-speed Weigh-in-motion System in order to enhance efficiency of weight enforcement, and to analyze patterns of overloaded trucks on highways through the system. Furthermore, it is to review possibilities of developing overweight control system with application of the HS-WIM system. The HS-WIM system developed by this study consists of two sets of an axle load sensor, a loop sensor and a wandering sensor on each lane. A wandering sensor detects whether a travelling vehicle is off the lane or not with the function of checking the location of tire imprint. The sensor of the WIM system has better function of classifying types of vehicles than other existing systems by detecting wheel distance and tire type such as single or dual tire. As a result, its measurement errors regarding 12 types of vehicle classification are very low, which is an advantage of the sensor. The verification tests of the system under all conditions showed that the mean measurement errors of axle weight and gross axle weight were within 15 percent and 7 percent respectively. According to the WIM rate standard of the COST-323, the WIM system of this study is ranked at B(10). It means the system is appropriate for the purpose of design, maintenance and valuation of road infrastructure. The WIM system in testing a 5-axle cargo truck, the most frequently overloaded vehicle among 12 types of vehicles, is ranked at A(5) which means the system is available to control overloaded vehicles. In this case, the measurement errors of axle load and gross axle load were within 8 percent and 5 percent respectively. Weight analysis of all types of vehicles on highways showed that the most frequently overloaded vehicles were type 5, 6, 7 and 12 among 12 vehicle types. As a result, it is necessary to use more effective overweight enforcement system for vehicles which are seriously overloaded due to their lift axles. Traffic volume data depending upon vehicle types is basic information for road design and construction, maintenance, analysis of traffic flow, road policies as well as research.

• The KIPS Transactions:PartD
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• v.15D no.2
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• pp.223-234
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• 2008

Recently the web service area provides the efficient integrated environment of the internal and external of corporation and enterprise that wants the introduction of it is increasing. Also the web service develops and the new business model appears, the domestic enterprise environment and e-business environment are changing caused by web service. The web service which provides the similar function increases, most the method which searches the suitable service in demand of the user is more considered seriously. When it needs to choose one among the similar web services, service consumer generally needs quality information of web service. The problem, however, is that the advertised QoS information of a web service is not always trustworthy. A service provider may publish inaccurate QoS information to attract more customers, or the published QoS information may be out of date. Allowing current customers to rate the QoS they receive from a web service, and making these ratings public, can provide new customers with valuable information on how to rank services. This paper suggests the agent-based quality broker architecture which helps to find a service providing the optimum quality that the consumer needs in a position of service consumer. It is able to solve problem which modify quality requirements of the consumer from providing the architecture it selects a web service to consumer dynamically. Namely, the consumer is able to search the service which provides the optimal quality criteria through UDDI browser which is connected in quality broker server. To quality criteria value decision of each service the user intervention is excluded the maximum. In the existing selection architecture, the objective evaluation was difficult in subjective class of service selecting of the consumer. But the proposal architecture is able to secure an objectivity with the quality criteria value decision where the agent monitors binding information in consumer location. Namely, it solves QoS information of service which provider does not provide with QoS information sharing which is caused by with feedback of consumer side agents.

• Korean Journal of Agricultural Science
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• v.5 no.1
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• pp.15-28
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• 1978

It has been known that the shear strength of soil is an important design parameter for the foundation of structures, the retaining walls, the slope failures and so forth. In this study, the shear test was performed by using the direct shear apparatus under various degree of the moisture content and the density of the sample soils. The results of the study were summarized as follows; 1. The shear strength of soil increased with increase in the dry density of soil, and at the same level of density of the sample the shear strength of soil showed large values on a good grading of the sample. 2. The cohesion of the soil varied directly with the dry density of it, however the internal friction angle of soil was not affected by the dry density of tile sample. 3. The shear strength of sample varied inversly with the moisture content of it, and this phenomenon was apparent on a good grad ing of sample. 4. The cohesion of soil showed maximum value when the moisture content of the soil reached optimum level and the internal friction angle decreased with increase in the moisture content of it. These phenomena were very obvious on a good grading sample, SDC-1. 5. The cohesion of the soil decreased with increase in void ratio of the sample, but the internal friction angle of the sample didn't show such tendency.

• Journal of Korean Society of Forest Science
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• v.90 no.4
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• pp.420-430
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• 2001

The object of this study is to develop a computer program for the arrangement of the forest-road network maximizing the investment effect in forest-road construction with factors such as terrains, forest physiognomy, management plan, logging system, cost of forest-road construction, capacity of inputted labour, capacity of timber production and so on. The operating system developed by this study is Korean Windows 95/98 and Microsoft Visual Basic ver. 5.0. User interface was designed as systematic structure, it is presented as a kind of GUI(graphic user interface). The developed program has result of the most suitable forest-road arrangement, has suitable forest-road density calculated with cost of logging, cost of forest-road construction, diversion ratio of forest-road, cost of walking in forest. And the most suitable forest-road arrangement was designed for forest-road arrangement network which maximized investment effect through minimizing the sum of cost of logging and cost of forest-road construction. Input data were divided into map data and control data. Digital terrain model, division of forest-road layout plan, division of forest function and the existing road network are obtained from map data. on the other hand, cost of logging related terrain division, diversion ratio of forest-road and working road, cost of forest-road construction, cost of walking, cost of labor, walking speed, capacity of inputted labor, capacity of timber production and total distance of forest-road are inputted from control data. And map data was designed to be inputted by mesh method for common matrix. This program can be used to construct a new forest-road or vice forest-road which compensate already existing forest-road for the functional forestry.

• Journal of Radiation Protection and Research
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• v.39 no.1
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• pp.21-29
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• 2014

A new cold neutron triple-axis spectrometer (Cold-TAS) was recently constructed at the 30 MWth research reactor, HANARO. The spectrometer, which is composed of neutron optical components and radiation shield, required a redesign of the segmented monochromator shield due to the lack of adequate support of its weight. To shed some weight, lowering the height of the segmented shield was suggested while adding more radiation shield to the top cover of the monochromator chamber. To investigate the radiological effect of such change, we performed MCNPX simulations of a few different configurations of the Cold-TAS monochromator shield and obtained neutron and photon intensities at 5 reference points just outside the shield. Reducing the 35% of the height of the segmented shield and locating lead 10 cm from the bottom of the top cover made of polyethylene was shown to perform just as well as the original configuration as radiation shield excepting gamma flux at two points. Using gamma map by MCNPX, it was checked that is distribution of gamma. Increased flux had direction to the top and it had longer distance from top of segmented shield. However, because of reducing the 35% of the height, height of dissipated gamma was lower than original geometry. Reducing the 35% of the height of the segmented shield and locating lead 10cm from the bottom of the top cover was selected. After changing geometry, radiation dose was measured by TLD for confirming tester's safety at any condition. Neutron(0.21 ${\mu}Svhr^{-1}$) and gamma(3.69 ${\mu}Svhr^{-1}$) radiation dose were satisfied standard(6.25 ${\mu}Svhr^{-1}$).

• Information Systems Review
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• v.16 no.3
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• pp.161-177
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• 2014

Corporate credit rating assessment consists of complicated processes in which various factors describing a company are taken into consideration. Such assessment is known to be very expensive since domain experts should be employed to assess the ratings. As a result, the data-driven corporate credit rating prediction using statistical and artificial intelligence (AI) techniques has received considerable attention from researchers and practitioners. In particular, statistical methods such as multiple discriminant analysis (MDA) and multinomial logistic regression analysis (MLOGIT), and AI methods including case-based reasoning (CBR), artificial neural network (ANN), and multiclass support vector machine (MSVM) have been applied to corporate credit rating.2) Among them, MSVM has recently become popular because of its robustness and high prediction accuracy. In this study, we propose a novel optimized MSVM model, and appy it to corporate credit rating prediction in order to enhance the accuracy. Our model, named 'GAMSVM (Genetic Algorithm-optimized Multiclass Support Vector Machine),' is designed to simultaneously optimize the kernel parameters and the feature subset selection. Prior studies like Lorena and de Carvalho (2008), and Chatterjee (2013) show that proper kernel parameters may improve the performance of MSVMs. Also, the results from the studies such as Shieh and Yang (2008) and Chatterjee (2013) imply that appropriate feature selection may lead to higher prediction accuracy. Based on these prior studies, we propose to apply GAMSVM to corporate credit rating prediction. As a tool for optimizing the kernel parameters and the feature subset selection, we suggest genetic algorithm (GA). GA is known as an efficient and effective search method that attempts to simulate the biological evolution phenomenon. By applying genetic operations such as selection, crossover, and mutation, it is designed to gradually improve the search results. Especially, mutation operator prevents GA from falling into the local optima, thus we can find the globally optimal or near-optimal solution using it. GA has popularly been applied to search optimal parameters or feature subset selections of AI techniques including MSVM. With these reasons, we also adopt GA as an optimization tool. To empirically validate the usefulness of GAMSVM, we applied it to a real-world case of credit rating in Korea. Our application is in bond rating, which is the most frequently studied area of credit rating for specific debt issues or other financial obligations. The experimental dataset was collected from a large credit rating company in South Korea. It contained 39 financial ratios of 1,295 companies in the manufacturing industry, and their credit ratings. Using various statistical methods including the one-way ANOVA and the stepwise MDA, we selected 14 financial ratios as the candidate independent variables. The dependent variable, i.e. credit rating, was labeled as four classes: 1(A1); 2(A2); 3(A3); 4(B and C). 80 percent of total data for each class was used for training, and remaining 20 percent was used for validation. And, to overcome small sample size, we applied five-fold cross validation to our dataset. In order to examine the competitiveness of the proposed model, we also experimented several comparative models including MDA, MLOGIT, CBR, ANN and MSVM. In case of MSVM, we adopted One-Against-One (OAO) and DAGSVM (Directed Acyclic Graph SVM) approaches because they are known to be the most accurate approaches among various MSVM approaches. GAMSVM was implemented using LIBSVM-an open-source software, and Evolver 5.5-a commercial software enables GA. Other comparative models were experimented using various statistical and AI packages such as SPSS for Windows, Neuroshell, and Microsoft Excel VBA (Visual Basic for Applications). Experimental results showed that the proposed model-GAMSVM-outperformed all the competitive models. In addition, the model was found to use less independent variables, but to show higher accuracy. In our experiments, five variables such as X7 (total debt), X9 (sales per employee), X13 (years after founded), X15 (accumulated earning to total asset), and X39 (the index related to the cash flows from operating activity) were found to be the most important factors in predicting the corporate credit ratings. However, the values of the finally selected kernel parameters were found to be almost same among the data subsets. To examine whether the predictive performance of GAMSVM was significantly greater than those of other models, we used the McNemar test. As a result, we found that GAMSVM was better than MDA, MLOGIT, CBR, and ANN at the 1% significance level, and better than OAO and DAGSVM at the 5% significance level.

• Journal of the Korean Society of Groundwater Environment
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• v.7 no.3
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• pp.103-115
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• 2000

The formation of brown-colored precipitates is one of the serious problems frequently encountered in the development and supply of groundwater in Korea, because by it the water exceeds the drinking water standard in terms of color. taste. turbidity and dissolved iron concentration and of often results in scaling problem within the water supplying system. In groundwaters from the Pajoo area, brown precipitates are typically formed in a few hours after pumping-out. In this paper we examine the process of the brown precipitates' formation using the equilibrium thermodynamic and kinetic approaches, in order to understand the origin and geochemical pathway of the generation of turbidity in groundwater. The results of this study are used to suggest not only the proper pumping technique to minimize the formation of precipitates but also the optimal design of water treatment methods to improve the water quality. The bed-rock groundwater in the Pajoo area belongs to the Ca-$HCO_3$type that was evolved through water/rock (gneiss) interaction. Based on SEM-EDS and XRD analyses, the precipitates are identified as an amorphous, Fe-bearing oxides or hydroxides. By the use of multi-step filtration with pore sizes of 6, 4, 1, 0.45 and 0.2 $\mu\textrm{m}$, the precipitates mostly fall in the colloidal size (1 to 0.45 $\mu\textrm{m}$) but are concentrated (about 81%) in the range of 1 to 6 $\mu\textrm{m}$in teams of mass (weight) distribution. Large amounts of dissolved iron were possibly originated from dissolution of clinochlore in cataclasite which contains high amounts of Fe (up to 3 wt.%). The calculation of saturation index (using a computer code PHREEQC), as well as the examination of pH-Eh stability relations, also indicate that the final precipitates are Fe-oxy-hydroxide that is formed by the change of water chemistry (mainly, oxidation) due to the exposure to oxygen during the pumping-out of Fe(II)-bearing, reduced groundwater. After pumping-out, the groundwater shows the progressive decreases of pH, DO and alkalinity with elapsed time. However, turbidity increases and then decreases with time. The decrease of dissolved Fe concentration as a function of elapsed time after pumping-out is expressed as a regression equation Fe(II)=10.l exp(-0.0009t). The oxidation reaction due to the influx of free oxygen during the pumping and storage of groundwater results in the formation of brown precipitates, which is dependent on time, $Po_2$and pH. In order to obtain drinkable water quality, therefore, the precipitates should be removed by filtering after the stepwise storage and aeration in tanks with sufficient volume for sufficient time. Particle size distribution data also suggest that step-wise filtration would be cost-effective. To minimize the scaling within wells, the continued (if possible) pumping within the optimum pumping rate is recommended because this technique will be most effective for minimizing the mixing between deep Fe(II)-rich water and shallow $O_2$-rich water. The simultaneous pumping of shallow $O_2$-rich water in different wells is also recommended.

• Composites Research
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• v.34 no.4
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• pp.241-248
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• 2021

As the electric vehicle market grows, there is an issue of light weight vehicles to increase battery efficiency. Therefore, it is going to replace the battery module cover that protects the battery module of electric vehicles with high strength/high heat-resistant polymer composite material which has lighter weight from existing aluminum materials. It also aims to respond to the early electric vehicle market where technology changes quickly by combining 3D printing technology that is advantageous for small production of multiple varieties without restrictions on complex shapes. Based on the composite material mechanics, the critical length of glass fibers in short glass fiber (GF)/polycarbonate (PC) composite materials manufactured through extruder was derived as 453.87 ㎛, and the side feeding method was adopted to improve the residual fiber length from 365.87 ㎛ and to increase a dispersibility. Thus, the optimal properties of tensile strength 135 MPa and Young's modulus 7.8 MPa were implemented as GF/PC composite materials containing 30 wt% of GF. In addition, the filament extrusion conditions (temperature, extrusion speed) were optimized to meet the commercial filament specification of 1.75 mm thickness and 0.05 mm standard deviation. Through manufactured filaments, 3D printing process conditions (temperature, printing speed) were optimized by multi-optimization that minimize porosity, maximize tensile strength, and printing speed to increase the productivity. Through this procedure, tensile strength and elastic modulus were improved 11%, 56% respectively. Also, by post-processing, tensile strength and Young's modulus were improved 5%, 18% respectively. Lastly, using the FEA (finite element analysis) technique, the structure of the battery module cover was optimized to meet the mechanical shock test criteria of the electric vehicle battery module cover (ISO-12405), and it is satisfied the battery cover mechanical shock test while achieving 37% lighter weight compared to aluminum battery module cover. Based on this research, it is expected that 3D printing technology of polymer composite materials can be used in various fields in the future.

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.4
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• pp.94-106
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• 2022

In order to increase timber self-sufficiency, Korea's 6th Basic Forest Plan aims to increase the density of forest roads to 12.8 m ha^-1 by 2037. However, due to rapid re-forestation, current management infrastructure is insufficient, with just 4.8 m ha^-1 of forest roads in 2017. This is partly due to time and cost limitations on the process of forest road feasibility evaluation, which considers factors such as topography and forest conditions. To solve this problem, we propose an eco-friendly and efficient forest road network planning method using a geographic information system (GIS), which can evaluate a potential road site remotely based on spatial information. To facilitate such planning, this study identifies forest road construction priorities that can be evaluated using spatial information, such as topography, forest type and forest disasters. A method of predicting the optimal route to connect a forest road with existing roads is also derived. Overlapping analysis was performed using GIS-MCE (which combines GIS with multi-criteria evaluation), targeting the areas of Cheongsong-gun and Buk-gu, Pohang-si, which have a low forest-road density. Each factor affecting the suitability of a proposed new forest road site was assigned a cost, creating a cost surface that facilitates prioritization for each forest type. The forest path's optimal route was then derived using least-cost path analysis. The results of this process were 30 forestry site recommendations in Cheongsong-gun and one in Buk-gu, Pohang-si; this would increase forest road density for the managed forest sites in Cheongsong-gun from 1.58 m ha^-1 to 2.55 m ha^-1. This evaluation method can contribute to the policy of increasing timber self-sufficiency by providing clear guidelines for selecting forest road construction sites and predicting optimal connections to the existing road network.