A large amount of small and medium-sized metal waste is generated during the decommissioning of nuclear power plants (NPPs). Metal waste is mostly contaminated with low-level radioactive, so it needs decontamination for self-disposal and recycling. A large amount of Organic Decontamination Liquid Waste during decontamination will be generated. The generated organic liquid waste is low in concentration, so the decomposition efficiency is low in the decomposition process. A conditioning process is necessary to concentrate at a high concentration. For effective treatment for Organic Decontamination Liquid Waste, the composition of organic liquid waste and conditioning process were analyzed. Organic acids, metal ions, radioactive nuclides, surfactants, etc. are present in the Organic Decontamination Liquid Waste, and suspended solids are sometimes generated by various reactions. According to previous studies, the concentration of organic acids including surfactants obtained results from several tens of ppm to a maximum of 1,000 ppm, so the maximum value of 1,000 ppm was assumed. For the composition and total amount of metal ions, the average value (52.7wt% Fe, 16.3wt% Ni, 15.1wt% Cr, 15.9wt% Mn) of the distribution of metal species removed by the actual decontamination process is applied, and the total amount is 1,000 ppm was assumed. As for the radionuclides, only 60Co and 137Cs, which are expected to be mainly present, were considered, and 60Co was assumed to be 2,000 Bq/g and 137Cs to be 360 Bq/g by referring to the literature. The amounts of suspended solids were assumed to be 500 ppm by referring to the characteristics of the liquid waste generated in the decontamination process of the NPPs. Based on the estimated value, a reaction formula was established and a simulated Organic Decontamination Liquid Waste was prepared. As a result of measurement using an analysis device, the composition of the estimated and simulated Organic Decontamination Liquid Waste had similar values. The conditioning and treatment process largely consists of pretreatment, conditioning, decomposition processes. Organic Decontamination Liquid Waste goes through a pretreatment process to remove impurities with large particles. In the conditioning process, treated water that has passed through the UF/RO membrane system is discharged into the environment. At this time, Concentrated water goes through a decomposition process for processing the Organic Decontamination Liquid Waste, and is discharged to the environment through a secondary RO membrane system. The conditioning process is the low-concentration Organic Decontamination Liquid Waste in the UF membrane system is forming a micelles in an RO membrane system, concentrating it to a high concentration and then go through a recirculation process in the UF membrane system. An experiment was conducted to confirm whether the concentration of surfactants occurred during the conditioning process. As a result of the experiment confirmed that the highly concentrated surfactant formed micelles and was filtered out in the UF membrane system.

Organic waste generated by small and medium-sized (S&M-sized) metal decontamination in NPP decommissioning. To lower the concentration of these organic substances for a level acceptable at the disposal site, the project of “Development of Treatment Process of Organic Decontamination Liquid Wastes from Decommissioning of Nuclear Power Plants” is being carried out. The conditioning and treatment process of organic liquid waste was designed. Also, the literature was investigated to make simulated organic liquid waste, and the composition of these waste was analyzed and compared. As the decontamination agent, organic acids such as EDTA, oxalic acid, citric acid are used. The sum of the concentrations of these organic materials was set to a maximum value of 1,000 ppm. The major metal ions of the decontamination liquid waste estimated are 59Fe, 51Cr, 54Mn, 63Ni, and the concentrations are respectively 527, 163, 161, 159 ppm. Additional major metal ions are 60Co, 58Co, 137Cs. 58Co is replaced by 60Co because it has the same chemical properties as 60Co. Unlike the HLW, the contamination level of S&M-sized metal in primary system was quite low, so 60Co is set to 2,000 Bq/g. Considering the contribution of fission and gamma ray dose constant, 137Cs was estimated to 360 Bq/g. Also, suspended solids of decontamination liquid waste were set at 500 ppm. Under these assumptions, the simulated organic liquid waste was made, and then organic substances and metal ions were analyzed with TOC analyzer and ICP-OES. The TOC analysis value was expected to 392 ppm in consideration of the equivalent organic quantity. the test result was 302 ppm. Some of organics appears to have been decomposed by acid. The values of metal ions (Fe3+, Cr3+, Mn2+, Ni2+) analyzed by ICP-OES are 139, 4, 152, 158 ppm, respectively. A large amount of Cr3+ and Fe3+ were expected to exist as ions, but they existed in the form of suspended solid. Mn2+ and Ni2+ came out similar to the expected values. The designed conditioning and treatment process is largely divided into pretreatment, conditioning, and decomposition processes. After collecting in the primary liquid waste storage tank, large particulate impurities and suspensions are removed through a pretreatment process. In the conditioning process, treated liquid waste passes through UF/RO membrane system, and pure water is discharged to the environment after monitoring. Concentrated water is decomposed in the electrochemical catalyst decomposition process, then this water secondarily passes through the RO membrane system and then discharged to the environment after monitoring. Through an additional experiment, the conditioning and treatment process will be verified.

In this paper, we utilize a Gaussian process to predict the power consumption in the air-conditioning system. As the power consumption in the air-conditioning system takes a form of a time-series and the prediction of the power consumption becomes very important from the perspective of the efficient energy management, it is worth to investigate the time-series model for the prediction of the power consumption. To this end, we apply the Gaussian process to predict the power consumption, in which the Gaussian process provides a prior probability to every possible function and higher probabilities are given to functions that are more likely consistent with the empirical data. We also discuss how to estimate the hyper-parameters, which are parameters in the covariance function of the Gaussian process model. We estimated the hyper-parameters with two different methods (marginal likelihood and leave-one-out cross validation) and obtained a model that pertinently describes the data and the results are more or less independent of the estimation method of hyper-parameters. We validated the prediction results by the error analysis of the mean relative error and the mean absolute error. The mean relative error analysis showed that about 3.4% of the predicted value came from the error, and the mean absolute error analysis confirmed that the error in within the standard deviation of the predicted value. We also adopt the non-parametric Wilcoxon’s sign-rank test to assess the fitness of the proposed model and found that the null hypothesis of uniformity was accepted under the significance level of 5%. These results can be applied to a more elaborate control of the power consumption in the air-conditioning system.