• Advances in environmental research
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• v.4 no.3
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• pp.155-172
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• 2015

In this study, a complete set of recirculating cooling water system and the required instruments were built in a semi-industrial-scale and a 50 g/h ozone generation plant and a chlorine system were designed for cooling water treatment. Both chlorination and ozonation treatment methods were studied and the results were analyzed during two 45-days periods. The concentrations of ozone and chlorine in recirculating water were constant at 0.1 mg/lit and 0.6 mg/lit, respectively. In ozone treatment, by increasing the concentration cycle to 33%, the total water consumption decreased by 26% while 11.5% higher energy efficiency achieved thanks to a better elimination of bio-films. In case of Carbon Steel, the corrosion rate reached to 0.012 mm/yr and 0.025 mm/yr for the ozonation and chlorination processes, respectively. Furthermore, consumptions of the anti-corrosion and anti-sedimentation materials in the ozone cooling water treatment were reduced about 60% without using any oxidant and non-oxidant biocides. No significant changes in sediment load were seen in ozonation compared to chlorination. The Chemical Oxygen Demand of the blow-down in ozonation method decreased to one-sixth of that in the chlorination method. Moreover, the soluble iron and water turbidity in the ozonation method were reduced by 97.5% and 70%, respectively. Although no anaerobic bacteria were seen in the cooling water at the proper concentration range of ozone and chlorine, the aerobic bacteria in chlorine and ozone treatment methods were 900 and 200 CFU/ml, respectively. The results showed that the payback time for the ozone treatment is about 2.6 years.

• Resources Recycling
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• v.23 no.3
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• pp.3-12
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• 2014

This study aims at providing an economic assessment for incineration plants which recover heat during its incineration process. In this study, Life Cycle Cost(LCC) of incineration plants is performed based on each regression analysis formula for construction cost, operation cost, and heat generation in order to compare economic feasibility. The result shows that the incineration plant recovering waste heat while processing 80 tons of waste per day increases both initial investment and operation cost but this type of an incineration plant has economical predominance from the recovered waste heat over the one that does not recover heat when being operated for more than eleven years if the retrieved heat replaces the use of LNG. And its payback time reaches more than 19 years in case of selling heat and performing emission trading.

• Journal of the Korean Solar Energy Society
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• v.31 no.2
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• pp.135-142
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• 2011

Architectural market in the world is trying to develop Zero Carbon Buildng that doesn"t use fossil fuel. Residential building that thermal load such as heating and domestic hot water is over 70% in energy consumption is easy to make Zero Carbon Building compared with office building that is mainly electric load. So, As a preliminary for analyzing the effect of Solar thermal system in the building, an annual energy consumption of residential building and total heat loads are calculated. Based on this result, three alternatives of solar thermal system for hot water and heating are applied in the building while installation area is increasing. Solar thermal system is applied on balcony and roof of apartment building as the way to reduce thermal load. In the first case that solar thermal system for hot water is applied on the balcony, optimum installation area is $56m^2$. And you could install $40m^2$ of this system in the roof that angle is $30^{\circ}$. In the second case of solar thermal system for heating and hot water, you can install $40m^2$ on the roof. As a result of economic evaluation, the most economical application method is to install $40m^2$ of solar thermal system for only hot water on the roof of the building. At that time, you can payback the initial investing cost within 10 years. And carbon emission of this method can be reduced until about 4 ton per year.

• International Journal of Computer Science & Network Security
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• v.21 no.8
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• pp.141-148
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• 2021

Project management is a current trend of management in the public sphere, based on different principles, methods and tools. The tools include information technologies providing control over time, cost, quality and planning process in order to ensure accountability to interested parties. The goal of the research was to examine the impact of the integration of information systems in project management of the public sphere on the quality of public governance and administration using the example of infrastructure projects involving the private sector in developing countries. The methodology of the research is based on the concepts of "digital-era governance" (DEG), "Information governance" and "project governance" to determine the effectiveness of information systems and technologies in the management of infrastructure projects in the public sphere. The data from the countries with Lower middle income (India, Indonesia, Philippines, Ukraine, Vietnam) and Upper middle income (Argentina, Brazil, China, Colombia, Mexico, Peru, Romania, Russian Federation, Thailand, Turkey) for 1996-2020 were used to study the effects of DEG. The results show two main trends in the countries with Lower middle income and Upper middle income. The first trend is the development of digital governance, the concept of "digital-era governance" through information systems and performance measurement of the governance system, forecasting of investment flows of infrastructure projects, measurement of payback and effectiveness parameters for investment management in the public sector, decision support. The second trend is the existence of systemic challenges related to corruption, social and institutional factors through the development of democracy in developing countries and the integration of NPM similar to developed countries. The confidence of interested parties, especially private investors, in public authorities is determined by other factors - the level of return on investment, risks and assignment of responsibility, probability of successful completion of the project. These data still remain limited for a wide range of project participants, including citizens.

• Nuclear Engineering and Technology
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• v.53 no.7
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• pp.2418-2425
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• 2021

Monazite is a phosphate mineral that contains thorium (Th) and rare earth elements. The Th concentration in monazite can be as high as 500 ppm, and it has the potential to be used as fuel in the nuclear power system. Therefore, this study aimed to conduct the techno-economic analysis (TEA) of Th extraction in the form of thorium oxide (ThO₂) from monazite. Th can be extracted from monazite through an alkaline fusion method. The TEA of ThO₂ production studied parameters, including raw materials, equipment costs, total plant direct and indirect costs, and direct fixed capital cost. These parameters were calculated for the production of 0.5, 1, and 10 ton ThO₂ per batch. The TEA study revealed that the highest production cost was ascribed to installed equipment. Furthermore, the highest return on investment (ROI) of 21.92% was achieved for extraction of 1 ton/batch of ThO₂, with a payback time of 4.56 years. With further increase in ThO₂ production to 10 ton/batch, the ROI was decreased to 5.37%. This is mainly due to a significant increase in the total capital investment with increasing ThO₂ production scale. The minimum unit production cost was achieved for 1 ton ThO₂/batch equal to 335.79 $/Kg ThO₂.

• Korean Journal of Construction Engineering and Management
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• v.13 no.5
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• pp.103-112
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• 2012

Republic of Korea is recently becoming an advanced country with increasing standard of living. This is causing a lack of employment in the construction industry because of high labor costs and it is resulting rapid increase in foreign labors. Modular Method of Construction can be defined as 50%~90% of the entire process is completed in factory, and transferred to construction field to install. The main purpose of this process is to minimize the entire process that possibly can be done at construction field in order to maximize the quality. The current local usage of Modular Method of Construction started at Shin Ki Elementary School during 2003 and it is widely used for military facilities. It should be used more because it has strengths of spending short time period to complete and low production costs. It can make a change if Modular Method of Construction is applied. Toyota is currently producing vehicle with conveyor system and if Modular Method of Construction is applied, then it is possible to reduce the waste of labor, and automatic production time. Expansion of the modular Market can be expected by applying this method because it will improve producing costs, high quality, and enforced process. This research tried to solve the problem of factory's manufacturing production by applying local Modular Method of Construction to provide suggestions and analyze the profitability with applied conveyor system. It is depending on produced model, but this research's model will take 20 months including assessment of payback period.

• International Journal of Computer Science & Network Security
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• v.21 no.3
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• pp.245-256
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• 2021

Poor logistical infrastructure and agri-food supply chain management leads to significant food waste in logistic system. The concept of the sustainable value added agri-food chains requires defined approach to the analysis of the existing situation, possible improving strategies and also assessment of these changes impact on further development. The purpose of research is to provide scientific substantiation of theoretical and methodological principles and develop practical recommendations for the improvement of the agri-food logistics distribution system. A case study methodology is used in this article. The research framework is based on 4 steps: Value Stream Mapping (VSM), Gap and Process Analysis, Validation and Improvement Areas Definition and Imitation Modelling. This paper presents the appropriateness of LEAN logistics tools using, in particular, Value Stream Mapping (VSM) for minimizing logistic losses and Simulation Modeling of possible logistics distribution system improvement results. The algorithm of VSM analysis of the agri-food supply chain, which involves its optimization by implementing the principles of sustainable development at each stage, is proposed. The methodical approach to the analysis of possible ways for optimizing the operation of the logistics system of the agri-food distribution is developed. It involves the application of Value Stream Mapping, i.e. designing of stream maps of the creation of the added value in the agri-food supply chain for the current and future state based on the minimization of logistic losses. Simulation modeling of the investment project on time optimization in the agri-food supply chain and economic effect of proposed improvements in logistics product distribution system functioning at the level of the investigated agricultural enterprise has been determined. Improvement of logistics planning and coordination of operations in the supply chain and the innovative pre-cooling system proposed to be introduced have a 3-year payback period and almost 75-80% probability. Based on the conducted VSM analysis of losses in the agri-food supply chain, there have been determined the main points, where it is advisable to conduct optimization changes for the achievement of positive results and the significant economic effect from the proposed measures has been confirmed. In further studies, it is recommended to focus on identifying the synergistic effect of the agri-food supply chain optimization on the basis of sustainable development.

• 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.