• Journal of Environmental Science International
• /
• v.26 no.8
• /
• pp.955-966
• /
• 2017

Amendment of multi-binders was employed for the immobilization of metal(loid)s in field-contaminated soils to reduce the leaching potential. The effect of different types of multi-binders (lime/diammonium phosphate, diammonium phosphate/ladle slag and lime/ladle slag) on the solidification/stabilization of metal(loid)s (Pb, Zn, Cu and As) from the smelter soil and mine tailing soil were investigated. The amended soils were evaluated by measuring Toxicity Characterization Leaching Procedure (TCLP) leaching concentration of metal(loid)s. The results show that the leaching concentration of metal(loid)s decreased with the immobilization using multi-binders. In terms of TCLP extraction, the mixed binder was effective in the order of lime/ladle slag > diammonium phosphate/ladle slag > lime/diammonium phosphate. When the mixed binder amendment (0.15 g lime+0.15 g ladle slag for 1g smelter soil and 0.05 g lime+0.1 g ladle slag for 1 g mine tailing soil, respectively) was used, the leaching concentration of metal(loid)s decreased by 90%. However, As leaching concentration increased with diammonium phosphate/lime and diammonium phosphate/ladle slag amendment competitive anion exchange between arsenic ion and phosphate ion from diammonium phosphate. The Standard, Measurements and Testing programme (SM&T) analysis indicated that fraction 1 (F1, exchangeable fraction) decreased, while fraction 4 (F4, residual fraction) increased. The increased immobilization efficiency was attributed to the increase in the F4 of the SM&T extraction. From this work, it was possible to suggest that both arsenic and heavy metals can be simultaneously immobilized by the amendment of multi-binder such as lime/ladle slag.

• Transactions of the Korean Society of Mechanical Engineers B
• /
• v.23 no.10
• /
• pp.1327-1339
• /
• 1999

Characteristics of two-phase flow and heat transfer were numerically investigated in a submerged gas Injection system. Effects of both the gas flow rate and bubble size were investigated. In addition, heat transfer characteristic and effects of heat transfer were investigated when temperature of the injected gas was different from that of the liquid. The Eulerian approach was used for the formulation of both the continuous and the dispersed phases. The turbulence in the liquid phase was modeled by the use of the standard $k-{\varepsilon}$ turbulence model. The interphase friction and heat transfer coefficient were calculated by means of correlations available in the literature. The turbulent dispersion of the phases was modeled by introducing a "dispersion Prandtl number". The plume region and the axial velocities are increased with increases in the gas flow rate and with decreases in the bubble diameter. The turbulent flow field grows stronger with the increases in the gas flow rate and with the decreases in the bubble diameter. In case that the heat transfer between the liquid and the gas is considered, the axial and the radial velocities are decreased in comparison with the case that there is no temperature difference between the liquid and the gas when the temperature of the injected gas is higher than the mean liquid temperature. The results in the present research are of interest in the design and the operation of a wide variety of material and chemical processes.

• Applied Chemistry for Engineering
• /
• v.25 no.2
• /
• pp.181-187
• /
• 2014

In order to use the spherical atomizing reduction steel slag (ladle furnace slag, LFS) instead of the fine aggregate of polymer concrete composites, various specimens were prepared with various replacement ratios of atomizing reduction steel slag and the addition ratios of polymer binder. Physical properties of these specimens were investigated through the absorption test, the compressive strength test, the flexural strength test, the hot water resistance test, the pore analysis and the micro-structure using scanning electron microscope. Results showed that the compressive strength and flexural strength of specimens with 7.5% of polymer binders increased with the increase of replacement ratios of atomizing reduction steel slag, but those of the specimens with 8.0% or more of polymer binders showed a maximum strength at a certain replacement ratio due to the material segregation causing the increase of fluidity. By hot water resistance tests, the compressive strength, flexural strength, average pore diameter, and bulk density decreased but the total pore volume and pore diameter increased. It was concluded that the amount of polymer binders could be reduced by maximum 23.8%, because the workability of the polymer concrete was remarkably improved by using the atomizing reduction steel slag instead of fine aggregate. However, since the use of atomizing reduction steel slag decreased the resistance of the polymer concrete to hot water, further studies are required.

• Korean Chemical Engineering Research
• /
• v.53 no.3
• /
• pp.364-371
• /
• 2015

For the cost down of polymer concrete, It is very important to reduce the use amount of polymer binder, which occupies most of the production cost of polymer concrete. Fly ash and atomizing reduction steel slag are spherical materials obtained from industrial by-products. Spherical atomizing reduction steel slag was manufactured using steel slag from reduction process of ladle furnace by atomizing technology. To investigate the physical properties of polymer concrete, polymer concrete specimens were prepared with the various proportions of polymer binder and replacement ratios of atomizing steel slag. Results showed that compressive and flexural strengths of the specimens were remarkably increased with the addition amount of polymer binder and the replacement ratios of atomizing steel slag. In the hot water resistance test, compressive strength, flexural strength, bulk density and average pore diameter decreased but total pore volume and pore diameter increased. We found that polymer concrete developed in this study reduced the amount of polymer binder by 18.2% compared to the conventional product because of the remarkable improvement of workability of polymer concrete using spherical fly ash and atomizing reduction steel slag instead of calcium carbonate (filler) and river sand (fine aggregate).

• Journal of Intelligence and Information Systems
• /
• v.16 no.2
• /
• pp.19-32
• /
• 2010

Volatility plays a central role in both academic and practical applications, especially in pricing financial derivative products and trading volatility strategies. This study presents a novel mechanism based on generalized autoregressive conditional heteroskedasticity (GARCH) models that is able to enhance the performance of intelligent volatility trading systems by predicting Korean stock market volatility more accurately. In particular, we embedded the concept of the volatility asymmetry documented widely in the literature into our model. The newly developed Korean stock market volatility index of KOSPI 200, VKOSPI, is used as a volatility proxy. It is the price of a linear portfolio of the KOSPI 200 index options and measures the effect of the expectations of dealers and option traders on stock market volatility for 30 calendar days. The KOSPI 200 index options market started in 1997 and has become the most actively traded market in the world. Its trading volume is more than 10 million contracts a day and records the highest of all the stock index option markets. Therefore, analyzing the VKOSPI has great importance in understanding volatility inherent in option prices and can afford some trading ideas for futures and option dealers. Use of the VKOSPI as volatility proxy avoids statistical estimation problems associated with other measures of volatility since the VKOSPI is model-free expected volatility of market participants calculated directly from the transacted option prices. This study estimates the symmetric and asymmetric GARCH models for the KOSPI 200 index from January 2003 to December 2006 by the maximum likelihood procedure. Asymmetric GARCH models include GJR-GARCH model of Glosten, Jagannathan and Runke, exponential GARCH model of Nelson and power autoregressive conditional heteroskedasticity (ARCH) of Ding, Granger and Engle. Symmetric GARCH model indicates basic GARCH (1, 1). Tomorrow's forecasted value and change direction of stock market volatility are obtained by recursive GARCH specifications from January 2007 to December 2009 and are compared with the VKOSPI. Empirical results indicate that negative unanticipated returns increase volatility more than positive return shocks of equal magnitude decrease volatility, indicating the existence of volatility asymmetry in the Korean stock market. The point value and change direction of tomorrow VKOSPI are estimated and forecasted by GARCH models. Volatility trading system is developed using the forecasted change direction of the VKOSPI, that is, if tomorrow VKOSPI is expected to rise, a long straddle or strangle position is established. A short straddle or strangle position is taken if VKOSPI is expected to fall tomorrow. Total profit is calculated as the cumulative sum of the VKOSPI percentage change. If forecasted direction is correct, the absolute value of the VKOSPI percentage changes is added to trading profit. It is subtracted from the trading profit if forecasted direction is not correct. For the in-sample period, the power ARCH model best fits in a statistical metric, Mean Squared Prediction Error (MSPE), and the exponential GARCH model shows the highest Mean Correct Prediction (MCP). The power ARCH model best fits also for the out-of-sample period and provides the highest probability for the VKOSPI change direction tomorrow. Generally, the power ARCH model shows the best fit for the VKOSPI. All the GARCH models provide trading profits for volatility trading system and the exponential GARCH model shows the best performance, annual profit of 197.56%, during the in-sample period. The GARCH models present trading profits during the out-of-sample period except for the exponential GARCH model. During the out-of-sample period, the power ARCH model shows the largest annual trading profit of 38%. The volatility clustering and asymmetry found in this research are the reflection of volatility non-linearity. This further suggests that combining the asymmetric GARCH models and artificial neural networks can significantly enhance the performance of the suggested volatility trading system, since artificial neural networks have been shown to effectively model nonlinear relationships.