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The drinking water network serving Korea has been used for almost 100 years. Therefore, pipelines have suffered various degrees of deterioration due to aggressive environments. The pipe breaks were caused by in-external corrosion, water hammer, surface loading, etc. In this paper, we focused on describing corrosion status in water distribution pipes in Korea and reviewing some methods to predict corrosion rates. Results indicate that corrosive water of lakes was more aggressive than river water and the winter was more aggressive compared to other seasons. The roughness growth rates of Dongbok lake showed 0.23 mm/year. The high variation of corrosion rates is controlled by the aging pipes and smaller diameter. Also the phenolphthalein test on a cementitious core of cement mortar lined ductile cast iron pipe indicated the pipes over 15 years old had lost 50∼100% of their lime active cross sectional area. [ABSTRACT FROM AUTHOR]

An existing SBR plant in a rural area was retrofitted from a conventional fill-and-draw system to an intermittent-aeration system for additional nitrogen removal. This study indicated that organic and nitrogen removal efficiency was improved over that before the retrofitting. But effluent phosphorus concentration was increased gradually with the operating time. In the latter period of investigation, phosphorus concentration in effluent was higher than influent. It was regarded that an excessively accumulated phosphorus was released again under the anaerobic conditions of the sludge storage tank. The application of the electro-coagulation process was investigated as an alternative method in order to prevent phosphorus from re-releasing. A laboratory test for electro-coagulation indicated that T-P removal was more stable than the biological method only. In addition, it was confirmed that T-N and organic materials as well as T-P were removed simultaneously by the electrochemical reaction in the bioreactor combined with electrolysis by more than the bioreactor only. [ABSTRACT FROM AUTHOR]

To estimate true Brix and alcoholic strength of must and wines without distillation, a novel approach using a refractometer and a hydrometer was developed. Initial Brix (I.B.), apparent refractometer Brix (A.R.), and apparent hydrometer Brix (A.H.) of must were measured by refractometer and hydrometer, respectively. Alcohol content (A) was determined with a hydrometer after distillation and true Brix (T.B.) was measured in distilled wines using a refractometer. Strong proportional correlations among A.R., A.H., T.B., and A in sugar solutions containing varying alcohol concentrations were observed in preliminary experiments. Similar proportional relationships among the parameters were also observed in must, which is a far more complex system than the sugar solution. To estimate T.B. and A of must during alcoholic fermentation, a total of 6 planar equations were empirically derived from the relationships among the experimental parameters. The empirical equations were then tested to estimate T.B. and A in 17 wine products, and resulted in good estimations of both quality factors. This novel approach was rapid, easy, and practical for use in routine analyses or for monitoring quality of must during fermentation and final wine products in a winery and/or laboratory.

Taste and odour problems of tap water in Seoul are attributed to 2-methylisoborneol (2-MIB) and trans-1,10-dimethyl-trans-9-decalol (geosmin), which are the result of metabolism of algae and chlorine for disinfection. This study was carried out to measure 2-MIB and geosmin in the raw water from the Han River, to investigate removal efficiency of GAC and BAC integrated with post-ozonation, and to minimise and quantify the required chlorine concentration as a final disinfectant through the candidate process.

To predict daily water demand for Seoul, Korea, the artificial neural network (ANN) was used. For the cross correlation, the factors affecting water demand such as maximum temperature, humidity, and wind speed as natural factors, holidays as a social factor and daily demand 1 day before were used. From the results of learning using various hidden layers and units in order to establish the structure of optimal ANN, the case of 3 hidden layers and numbers of unit with the same number of input factors showed the best result and, therefore, it was applied to seasonal water demand prediction. The performance of ANN was compared with a multiple regression method. We discuss the representation ability of the model building process and the applicability of the ANN approach for the daily water demand prediction. ANN provided reasonable results for time series prediction.