• Korean Chemical Engineering Research
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• v.59 no.3
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• pp.345-358
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• 2021

This study focuses on the development of the liquid air production process that uses LNG (liquefied natural gas) cold energy which usually wasted during the regasification stage. The liquid air can be transported to the LNG exporter, and it can be utilized as the cold source to replace certain amount of refrigerant for the natural gas liquefaction. Therefore, the condition of the liquid air has to satisfy the available pressure of LNG storage tank. To satisfy pressure constraint of the membrane type LNG tank, proposed process is designed to produce liquid air at 1.3bar. In proposed process, the air is precooled by heat exchange with LNG and subcooled by nitrogen refrigeration cycle. When the amount of transported liquid air is as large as the capacity of the LNG carrier, it could be economical in terms of the transportation cost. In addition, larger liquid air can give more cold energy that can be used in natural gas liquefaction plant. To analyze the effect of the liquid air production amount, under the same LNG supply condition, the proposed process is simulated under 3 different air flow rate: 0.50 kg/s, 0.75 kg/s, 1.00 kg/s, correspond to Case1, Case2, and Case3, respectively. Each case was analyzed thermodynamically and economically. It shows a tendency that the more liquid air production, the more energy demanded per same mass of product as Case3 is 0.18kWh higher than Base case. In consequence the production cost per 1 kg liquid air in Case3 was $0.0172 higher. However, as liquid air production increases, the transportation cost per 1 kg liquid air has reduced by $0.0395. In terms of overall cost, Case 3 confirmed that liquid air can be produced and transported with $0.0223 less per kilogram than Base case.

• Economic and Environmental Geology
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• v.5 no.4
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• pp.187-209
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• 1972

Drilling position is one of the most important factors affecting on the blasting effects. There has been many reports on several blasting factors of burn-cut by Messrs. Brown and Cook, but in this study the author tried to compare drilling positions of burn-cut to pyramid-cut, and also to correlate burn-cut effects of drilling patterns, not being dealt by Prof. Ito in his theory, which emphasized on dynamical stress analysis between explosion and free face. According to former theories, there break out additional tensile stress reflected at the free face supplemented to primary compressive stress on the blasting with one-free-face. But with these experimented new drilling patterns of burn-cut, more free faces and nearer distance of each drilling holes make blasting effects greater than any other methods. To promote the above explosive effect rationary, it has to be considered two important categories under-mentioned. First, unloaded hole in the key holes should be drilled in wider diameter possibly so that it breaks out greater stress relief. Second, key holes possibly should have closer distances each other to result clean blasting. These two important factors derived from experiments with, theories of that the larger the dia of the unloaded hole, it can be allowed wider secondary free faces and closes distances of each holes make more developed stress relief, between loaded and unloaded holes. It was suggested that most ideal distance between holes is about 4 clearance in U. S. A., but the author, according to the experiments, it results that the less distance allow, the more effective blasting with increased broken rock volume and longer drifted length can be accomplished. Developed large hole burn-cut method aimed to increase drifting length technically under the above considerations, and progressive success resulted to achieve maximum 7 blasting cycles per day with 3.1m drifting length per cycle. This achievement originated high-speed-drifting works, and it was also proven that application of Metallic AN-FO on large hole burn-cut method overcomes resistance of one-free-face. AN-FO which was favored with low price and safety handling is the mixture of the fertilizer or industrial Ammonium-Nitrate and fuel oil, and it is also experienced that it shows insensible property before the initiation, but once it is initiated by the booster, it has equal explosive power of Ammonium Nitrate Explosives (ANE). There was many reports about AN-FO. On AN-FO mixing ratio, according to these experiments, prowdered AN-FO, 93.5 : 6.5 and prilled AN-FO 94 : 6, are the best ratios. Detonation, shock, and friction sensities are all more insensitive than any other explosives. Residual gas is not toxic, too. On initation and propagation of the detonation test, prilled AN-FO is more effective than powered AN-FO. AN-FO has the best explosion power at 7 days elapsed after it has mixed. While AN-FO was used at open pit in past years prior to other conditions, the author developed new improved explosives, Metallic AN-FO and Underwater explosive, based on the experiments of these fundmental characteristics by study on its usage utilizing AN-FO. Metallic AN-FO is the mixture of AN-FO and Al, Fe-Si powder, and Underwater explosive is made from usual explosive and AN-FO. The explanations about them are described in the other paper. In this study, it is confirmed that the blasting effects of utilizing AN-FO explosives are very good.

• Journal of Korean Society of Forest Science
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• v.30 no.1
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• pp.19-29
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• 1976

The fiberboard and paper mills in this country are much affected by the price hikes and shortage of phenolic resins, since phenolic acid as a raw material depends on imported good. It is prerequisite to fiberboard industry to help replace with other sized and stabilize the prices and supply of them, improving the quality of boards. Thus, the present study was carried out to examine the effect of strength increasing sized such as urea formaldehyde resin (anion and cation type) and urea melamine copolymer resin, on the quality of the wet forming hardboard, and comparing them with two types of proprietary modified melamine resins, and ordinary size, phenol resin. The Asplund pulp was prepared from wood wastes mixed with 20 percent of lauan and 80 percent of pines as a fibrous material. After sizing agents were added at a pH of 4.5 for 10 minutes with alum in the beater, the stock was made in the form of wet sheet, prepared, and then performed by hot pressing cycle: $180^{\circ}C$, $50-6-5kg/cm^2$, 1-2-7 minutes. The properties of hardboard were examined after air conditioning. The results obtained are summarized as follows: 1. There is a significant difference in specific gravity among hardboards that were treated with strength increasing resins, but no difference is effected by the increase in the resin content. In the case of modified melamine resin, its specific gravity is highest. The middle group comprises cation type of urea resin, anion type of urea resin, and acid colloid of urea-melamine copolymer resin. The lowest is phenolic resin. 2. The difference of the moisture content of hardboard both by the resins and by the amount of each resin applied is significant. The moisture content of hardboard becomes lower along with the increase of each resin content, but there is no difference between 2 and 3 percent. 3. For water absorption, there is a significant difference both in the adhesives used and in the amount of paraffin wax emulsion. The water resistance becomes higher inn proportion to the content of the paraffin wax emulsion. To satisfy KS F standards of the water resistance, a proprietary modified melamine resin (p-6100) and modified cation type of urea resin (p-1500) do not require any paraffin wax emulsion, but in the case of anion type of urea resin, cation type of urea resin, and urea-melamine copolymer resin, 1 percent of paraffin wax emulsion is needed, and 2 percent of paraffin wax emulsion in the case of phenolic resin. 4. The difference of flexural strength of hardboard both by the resins and by the amount of each resin is significant. Modified melamine resin shows the highest degree of flexural strength. Among the middle group are urea-melamine copolymer resin, p-1500, anion type of urea resin, and cation type of urea resin. Phenolic resin is the lowest. The cause may be attributable to factors combined with the pressing temperature, sizing effect, and thermal efficiency of press platens heated electrically. 5. Considering the economic advantages and properties of hardboard, it is proposed that urea-melamine copolymer resin and cation type of urea resin be used for the development of the fiberboard industry. It is desirable to further develop the modified urea-melamine copolymer resin and cation type of urea resin through continuous study.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.35-48
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• 2014

According to the 2013 construction market outlook report, the liquidation of construction companies is expected to continue due to the ongoing residential construction recession. Bankruptcies of construction companies have a greater social impact compared to other industries. However, due to the different nature of the capital structure and debt-to-equity ratio, it is more difficult to forecast construction companies' bankruptcies than that of companies in other industries. The construction industry operates on greater leverage, with high debt-to-equity ratios, and project cash flow focused on the second half. The economic cycle greatly influences construction companies. Therefore, downturns tend to rapidly increase the bankruptcy rates of construction companies. High leverage, coupled with increased bankruptcy rates, could lead to greater burdens on banks providing loans to construction companies. Nevertheless, the bankruptcy prediction model concentrated mainly on financial institutions, with rare construction-specific studies. The bankruptcy prediction model based on corporate finance data has been studied for some time in various ways. However, the model is intended for all companies in general, and it may not be appropriate for forecasting bankruptcies of construction companies, who typically have high liquidity risks. The construction industry is capital-intensive, operates on long timelines with large-scale investment projects, and has comparatively longer payback periods than in other industries. With its unique capital structure, it can be difficult to apply a model used to judge the financial risk of companies in general to those in the construction industry. Diverse studies of bankruptcy forecasting models based on a company's financial statements have been conducted for many years. The subjects of the model, however, were general firms, and the models may not be proper for accurately forecasting companies with disproportionately large liquidity risks, such as construction companies. The construction industry is capital-intensive, requiring significant investments in long-term projects, therefore to realize returns from the investment. The unique capital structure means that the same criteria used for other industries cannot be applied to effectively evaluate financial risk for construction firms. Altman Z-score was first published in 1968, and is commonly used as a bankruptcy forecasting model. It forecasts the likelihood of a company going bankrupt by using a simple formula, classifying the results into three categories, and evaluating the corporate status as dangerous, moderate, or safe. When a company falls into the "dangerous" category, it has a high likelihood of bankruptcy within two years, while those in the "safe" category have a low likelihood of bankruptcy. For companies in the "moderate" category, it is difficult to forecast the risk. Many of the construction firm cases in this study fell in the "moderate" category, which made it difficult to forecast their risk. Along with the development of machine learning using computers, recent studies of corporate bankruptcy forecasting have used this technology. Pattern recognition, a representative application area in machine learning, is applied to forecasting corporate bankruptcy, with patterns analyzed based on a company's financial information, and then judged as to whether the pattern belongs to the bankruptcy risk group or the safe group. The representative machine learning models previously used in bankruptcy forecasting are Artificial Neural Networks, Adaptive Boosting (AdaBoost) and, the Support Vector Machine (SVM). There are also many hybrid studies combining these models. Existing studies using the traditional Z-Score technique or bankruptcy prediction using machine learning focus on companies in non-specific industries. Therefore, the industry-specific characteristics of companies are not considered. In this paper, we confirm that adaptive boosting (AdaBoost) is the most appropriate forecasting model for construction companies by based on company size. We classified construction companies into three groups - large, medium, and small based on the company's capital. We analyzed the predictive ability of AdaBoost for each group of companies. The experimental results showed that AdaBoost has more predictive ability than the other models, especially for the group of large companies with capital of more than 50 billion won.