• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.44 no.4
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• pp.343-351
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• 2016

Cryogenic spray characteristics of a nitrogen swirl injector operating in supercritical environment have been numerically investigated. By comparing the equation of states(EOS) used for supercritical condition, SRK EOS was applied to predict the nitrogen thermodynamic property under supercritical environment. A Chung's method was implemented for the calculation of viscosity and conductivity and Takahashi's correlation based on Fuller's Theorem was implemented for the calculation of diffusion coefficient. By injecting the nitrogen with 5 bar differential pressure into 50 bar chamber filled with nitrogen, numerical simulation has been conducted. The dynamic Smagorinsky sub-grid scale (SGS) model has been compared with the algebraic Smagorinsky SGS model using FFT frequency analysis. The instability at the liquid film and gas core inside injector and the propagation of pressure oscillation into the injector has been investigated. The spreading angle of swirl injector obtained by numerical calculation has been validated with experimental result.

• The KIPS Transactions:PartB
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• v.11B no.2
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• pp.233-240
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• 2004

This paper presents a method to implicitly resolve ambiguities using dynamic incremental clustering in Korean-to-English and Japanese-to-English cross-language information retrieval (CLIR). The main objective of this paper shows that document clusters can effectively resolve the ambiguities tremendously increased in translated queries as well as take into account the context of all the terms in a document. In the framework we propose, a query in Korean/Japanese is first translated into English by looking up bilingual dictionaries, then documents are retrieved for the translated query terms based on the vector space retrieval model or the probabilistic retrieval model. For the top-ranked retrieved documents, query-oriented document clusters are incrementally created and the weight of each retrieved document is re-calculated by using the clusters. In the experiment based on TREC test collection, our method achieved 39.41% and 36.79% improvement for translated queries without ambiguity resolution in Korean-to-English CLIR, and 17.89% and 30.46% improvements in Japanese-to-English CLIR, on the vector space retrieval and on the probabilistic retrieval, respectively. Our method achieved 12.30% improvements for all translation queries, compared with blind feedback in Korean-to-English CLIR. These results indicate that cluster analysis help to resolve ambiguity.

• Journal of the Korean Society of Hazard Mitigation
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• v.10 no.6
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• pp.59-64
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• 2010

Building a firebreak against surface forest fire is a typical indirect suppression method that stops spread of flame by removing surface fuel, such as fallen leaves and bushes. In the sense of fire dynamic, building a firebreak is to set a section which will block thermal energy from igniting on virgin fuel. This study suggests and evaluates a calculation method for width of firebreak against surface fire for variant wind and slope conditions by applying the Point Source Model (PSM) to fallen leaves of Pinus densiflora. Width of firebreak was measured based on the distance the threshold radiant heat igniting Pinus densiflora fallen leaves at the heat flux of $4.9\;kW/m^2$ reaches. As a result, at the wind velocity of 0~5 m/s and on the slope of $0{\sim}50^{\circ}$, the appropriate width of a firebreak was 0.35~0.65 m for the mean flame height and 0.75~1.05 m for the maximum flame height. Accordingly, considering the factor of safety, the most appropriate width of a firebreak is 1.05 m based on the maximum flame height. Additional comparative analyses through experiments and field surveys are deemed necessary to determine appropriate widths of firebreak for different types of surface fuel.

• Journal of the Korea Concrete Institute
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• v.24 no.5
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• pp.559-566
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• 2012

In this study, fiber elements and a spring are used to build a reinforced concrete shear wall model. The fiber elements and the spring reflect flexural and shear behaviors of the shear wall, respectively. The fiber elements are built by inputting section data and material properties. The spring parameters representing strength and stiffness degradation, pinching, and slip were determined by comparing behaviors of fiber element and VecTor2 results. 'Pinching4' model in OpenSees is used for shear spring. The parameter selecting process for shear spring is a complicated and time consuming process. To study the applicability of the fiber element, reinforced concrete buildings containing a shear wall are evaluated using nonlinear dynamic analysis with various wall aspect ratio (H/L), various beam heights, and stiffness and flexural strength of beam and wall ratios. The aspect ratio of the wall showed distinct difference in IDR (interstory drift ratio) of the models with and without spring. On the other hand, the height of beam and ratio of stiffness and flexural strength of beam and wall did not show clear relation.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.18-18
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• 2011

Climate change is impacting and will increasingly impact both the quantity and quality of the world's water resources in a variety of ways. In some areas warming climate results in increased rainfall, surface runoff, and groundwater recharge while in others there may be declines in all of these. Water quality is described by a number of variables. Some are directly impacted by climate change. Temperature is an obvious example. Notably, increased atmospheric concentrations of $CO_2$ triggering climate change increase the $CO_2$ dissolving into water. This has manifold consequences including decreased pH and increased alkalinity, with resultant increases in dissolved concentrations of the minerals in geologic materials contacted by such water. Climate change is also expected to increase the number and intensity of extreme climate events, with related hydrologic changes. A simple framework has been developed in New Zealand for assessing and predicting climate change impacts on water resources. Assessment is largely based on trend analysis of historic data using the non-parametric Mann-Kendall method. Trend analysis requires long-term, regular monitoring data for both climate and hydrologic variables. Data quality is of primary importance and data gaps must be avoided. Quantitative prediction of climate change impacts on the quantity of water resources can be accomplished by computer modelling. This requires the serial coupling of various models. For example, regional downscaling of results from a world-wide general circulation model (GCM) can be used to forecast temperatures and precipitation for various emissions scenarios in specific catchments. Mechanistic or artificial intelligence modelling can then be used with these inputs to simulate climate change impacts over time, such as changes in streamflow, groundwater-surface water interactions, and changes in groundwater levels. The Waimea Plains catchment in New Zealand was selected for a test application of these assessment and prediction methods. This catchment is predicted to undergo relatively minor impacts due to climate change. All available climate and hydrologic databases were obtained and analyzed. These included climate (temperature, precipitation, solar radiation and sunshine hours, evapotranspiration, humidity, and cloud cover) and hydrologic (streamflow and quality and groundwater levels and quality) records. Results varied but there were indications of atmospheric temperature increasing, rainfall decreasing, streamflow decreasing, and groundwater level decreasing trends. Artificial intelligence modelling was applied to predict water usage, rainfall recharge of groundwater, and upstream flow for two regionally downscaled climate change scenarios (A1B and A2). The AI methods used were multi-layer perceptron (MLP) with extended Kalman filtering (EKF), genetic programming (GP), and a dynamic neuro-fuzzy local modelling system (DNFLMS), respectively. These were then used as inputs to a mechanistic groundwater flow-surface water interaction model (MODFLOW). A DNFLMS was also used to simulate downstream flow and groundwater levels for comparison with MODFLOW outputs. MODFLOW and DNFLMS outputs were consistent. They indicated declines in streamflow on the order of 21 to 23% for MODFLOW and DNFLMS (A1B scenario), respectively, and 27% in both cases for the A2 scenario under severe drought conditions by 2058-2059, with little if any change in groundwater levels.

• International Journal of Highway Engineering
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• v.8 no.3 s.29
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• pp.49-61
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• 2006

This study suggests long-life asphalt pavement method which can save maintenance cost by increasing the design and performance period of pavements. The high modulus asphalt binder developed and then various physical tests are performed. Laboratory performance tests and accelerated pavement test are conducted for the high modulus and conventional mixtures. The test results show that dynamic modulus values of high modulus mixtures are higher than those of the conventional mixtures, The high modulus mixtures yield better fatigue, rutting and moisture damage performance than conventional mixtures. Structural analysis is performed and a database is built up for long life asphalt pavement design. Pavement response model is developed through a multiple regression analysis program, SPSS using the database. A design software for the long life pavements is developed based on the pavement response model and laboratory and field performance tests results. In addition, optimum pavement sections and materials are suggested. The suggested AC thickness of long life asphalt pavement is 29cm. A Life cycle cost analysis(LCCA) is conducted to check the economical efficiency of the long life pavement section. The LCCA result shows that initial construction costs of long life and conventional pavements are almost equal, but long life pavement is more profitable in terms of the LCCA.

• International Area Studies Review
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• v.21 no.4
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• pp.223-245
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• 2017

This study is examined interaction between carbon market with stock market using a multivariate GARCH(DCC) model. Carbon market is EU ETS EUA price, stock market is the iron and cement stock price which has relatively energy intensive and massive carbon emissions sector in the industrial sector. It also analyzed changes in the correlation between the markets through an analysis of correlation coefficients. Moreover, it checked whether there was marketability expansion(or expansion of carbon emissions reduction) through the analysis above. As a result of empirical tests, it showed that the price spillover effect was insignificant. In addition, it represented that there was a weak correlation between the two markets since the volatility spillover effect disappeared in the second phase by an external shock(a financial crisis). Moreover, it was revealed that there were no significant changes although there was a weak upward trend in terms of the correlation between the carbon market and the stock market. This implies that emission rights could not expand marketability to financial market as a commodity(or did not play its natural role of the reduction of carbon emission).

• The Journal of the Acoustical Society of Korea
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• v.35 no.6
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• pp.480-490
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• 2016

As wind turbines become larger and lighter, they are likely to respond sensitively by dynamic loads applied on them. Since the responses at resonances are particularly interested, it is required to be able to predict natural frequencies of wind turbines reliably at early design stage. To achieve this, the foundation-soil analysis is needed to be carried out and a finite element approach is adopted in general. However, the finite element approach would not be appropriate in early design stage because it demands heavy efforts in pile-soil modelling and computing facilities. On the contrary, theoretical approaches adopting linear approximations for soils are relatively simple and easy to handle. Therefore, they would be a useful tool in predicting a pile-soil interaction, particularly in early design stage. In this study an analysis for a pile inserted in soil is performed. The pile and soil are modelled as a beam and continuum medium, respectively, within an elastic range. In this analysis, influence factors at the pile head for lateral loads are predicted by means of this continuum approach for various length-diameter ratios of the pile. The influence factors predicted are validated with those reported in literature, proposed from a finite element analysis.

• Journal of Korean Society of Steel Construction
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• v.25 no.4
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• pp.335-346
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• 2013

AASHTO LRFD and Korean Bridge Design Code (Limit State Design) specify to consider Truck and Lane load simultaneously determined from reliability-based live load model, and impact shall be applied to the truck load while it shall not be applied to the lane load. In this paper, vehicle-bridge interaction analysis under moving truck and lane loads were performed to estimate impact factor of the cables and girders for the selected multi-cable-stayed composite bridges with 230m, 400m and 540m main span. A 6-d.o.f. vehicle was used for truck load and a series of single-axle vehicles was applied to simulate equivalent lane load. The effect of damping ratio on the impact factor was estimated and then the essential parameters to impact factor, i.e., road surface roughness and vehicle speed were considered. The road surface roughness was randomly generated based on ISO 8608 and it was applied to the truck load only in the vehicle-bridge interaction analysis. The impact factors evaluated from dynamic interaction analysis were also compared with those by the influence line method that is currently used in design practice to estimate impact factor in cable-stayed bridge.

• Journal of Korean Society of Environmental Engineers
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• v.36 no.9
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• pp.641-647
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• 2014

In this study, sludge waste which has a difficulty in treating it was used to manufacture a fiber type of biosorbent. To solve the problems such as the release of organic pollutants and the difficulty in separating solid from treated water, entrapment method using Ca-alginate was used to immobilize sludge waste. Considering ease of manufacture as well as improvement of adsorptive ability, the biosorbent was manufactured in the form of fiber type. Optimum immobilization condition for minimizing the amount of alginate used and maximizing the performance of biosorbent was determined to be 10 g/L alginate concentration, 40 g/L sludge concentration, and 0.3-0.4 mm fiber diameter. The maximum Cd(II) uptake of the biosorbent was 60.73 mg/g. Pseudo-second-order kinetic model and Langmuir isotherm model adequately described the dynamic and equilibrium behaviors of Cd(II) biosorption onto the biosorbent, respectively. In conclusion, sludge waste generated from wastewater treatment process is a cheap raw material for the manufacture of biosorbent which can be used to remove toxic heavy metals from industrial wastewaters efficiently.