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This study is performed to evaluate the correlation of environmental factors for drinking water pipe deterioration using statistical analysis such as multiple regression, cluster analysis, discriminant analysis, and the adequacy and dependability of grouping factors used to deterioration prediction model. Results of this study are presented that high correlation related to pipe deterioration is showed not laying year of pipe but characteristic of surrounding area and analysis of chemical components. Therefore, major influence factors of pipe deterioration for types of cast iron pipe are product quality of pipe, environmental condition of laying area, and characteristics of soil and water quality. And grouping item of environmental factors using pipe deterioration evaluation model is classified to 4 types such as group related to pipe body and to hydraulic & water quality, and to characteristics of surrounding area, and to trouble & discontent of customer. And the very high adequacy of group classification is represented that the applied grouping items in this study are agree to previous studies.
It is well known that the adsorption character of activated carbon is dependent on the specific surface area and pore volume, but the relationship between the surface-chemical structure and the adsorption character has not been studied very often. The purpose of this study is to investigate the effect of the acidic surface functional groups of activated carbon and the adsorption characteristics of low concentration phenol. So three types of activated carbons and four different treatments were introduced to this isotherm experiment. These treatments were nontreatment, 1N HNO_3 treatment, 6N HNO_3 treatment, H_2O_2 treatment. The conclusions of this study are as followings. If the initial concentration of phenol is high as 5㎎/ℓ, the adsorption is dependent on the specific surface area. If the initial concentration of phenol is low as 100㎍/ℓ, the adsorption is dependent on the average pore volume. The acidic surface functional groups prevent the adsorption of phenol molecules to activated carbon. And the adsorbed amount decreases more for HNO_3 treatment than for H_2O_2 treatment and more for concentrated HNO_3 treatment than for dilute HNO_3 treatment.
Although the specific resistance to filtration is the most frequently employed means for characterizing dewaterability of a sludge, it presently is not possible to design nor to predict performance of dewatering facilities using traditional linearized parabolic filtration equation, that is, the specific resistance model because of theoretical and practical inadequacies of the concept. Limitations of the specific resistance model reflect the need to examine fundamental sludge properties and filtration behaviors affecting dewaterability. From this study, two major limitations of the specific resistance model were noted. First, specific resistance values are very dependent on the sludge concentration because of the variations of particle size distribution and cake clogging to occur when surface area mean diameter is less than 25㎛ for activated sludge, 18㎛ for water treatment plant sludge. Second, nonparabolic filtration behavior can result from cake clogging, caused by the migration of fine particles into the cake pores, accelated by skin effect with highly compressible sludges.
In this study, we examined the structural analysis of water demand fluctuation for water distribution control of water supply network. In order to analyze for the length of stationary time series, we calculate autocorrelation coefficient of each case equally divided data size. As a result, it was found that, with the data size of around three months, any case could be used as stationary time series. We analyze cross-correlation coefficient between the dialy watr consumption's data and primary influence factors. As a result, we have decided to use weather conditions and maximum temperature as natural primary factors and holidays as a social factor. Applying the multiple ARIMA model, we obtains an effective model to describe the daily water demand prediction. From the forecasting result, even though we forecast water distribution quantity of the following year, estimated values well express the fluctuations trend of measurements. Thus, the suitability of the model for practical use can be confirmed. When this model is used for practical water distribution control, water distribution quantity for the following day should be found by inputting maximum temperature and weather conditions obtained from weather forecast, and water purification plants and service reservoirs should be operated based on this information while operation of pumps and valves should be set up. Consequently, we will be able to devise a rational water management system.