• Proceedings of the Korea Water Resources Association Conference
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• 2004.05b
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• pp.90-101
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• 2004

The present trend of disposing treated sewage water by allowing it to infiltrate the soil brings a new dimension to environmental problems. It is therefore necessary to identify the chemicals likely to be present in treated sewage water. A soil column experiment was conducted to determine the behavior of chemical species in soil columns applied with secondary treated sewage water. To predict the behavior of chemical species, a multicomponent solute transport model that includes the biochemical redox process and cation exchange process was developed. The model computes changes in concentration over time caused by the processes of advection, dispersion, biochemical reactions and cation exchange reactions. The solute transport model was able to predict the behavior of the different chemical species. The model reproduced the sequential reduction reaction. To design the safe depth of plow layer where $NO_3^-$ is totally reduced, a numerical study of $NO_3^-$ leach was done and it was found out that the pore velocity and concentration of $CH_2O$ at the inject water was found to affect $NO_3^-$ reduction in the mobile pore water phase. It is revealed that the multicomponent solute transport model is useful to design the land treatment system for $NO_3^-$ removal from wastewater.

• Journal of Environmental Science International
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• v.31 no.12
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• pp.1051-1059
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• 2022

This study investigated microbial communities and their diversity in a full-scale mesophilic anaerobic digester treating sewage sludge. Influent sewage sludge and anaerobic digester samples collected from a wastewater treatment plant in Busan were analyzed using high-throughput sequencing. It was found that the microbial community structure and diversity in the anaerobic digester could be affected by inoculation effect with influent sewage sludge. Nevertheless, distinct microbial communities were identified as the dominant microbial communities in the anaerobic digester. Twelve genera were identified as abundant bacterial communities, which included several groups of syntrophic bacteria communities, such as Candidatus Cloacimonas, Cloacimonadaceae W5, Smithella, which are (potential) syntrophic-propionate-oxidizing bacteria and Mesotoga and Thermovigra, which are (potential) syntrophic-acetate-oxidizing bacteria. Lentimicrobium, the most abundant genus in the anaerobic digester, may contribute to the decomposition of carbohydrates and the production of volatile fatty acids during the anaerobic digestion of sewage sludge. Of the methanogens identified, Methanollinea, Candidatus Methanofastidiosum, Methanospirillum, and Methanoculleus were the dominant hydrogenotrophic methanogens, and Methanosaeta was the dominant aceticlastic methanogens. The findings may be used as a reference for developing microbial indicators to evaluate the process stability and process efficiency of the anaerobic digestion of sewage sludge.

• Applied Chemistry for Engineering
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• v.29 no.5
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• pp.613-619
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• 2018

In this study, various influent sludge pre-treatment methods and the internal recirculation of thickened sludge from effluents using a liquid/solid separation unit were adopted to investigate their effects on the sludge digestion and methane production in a combined mesophilic anaerobic and thermophilic aerobic sludge digestion process. A lab-scale combined sludge digestion process was operated during 5 phases using different feed sludge pre-treatment strategies. In phase 1, the feed sludge was pre-treated with a thermal-alkaline method. In contrast, in phases 2, 3 and 4, the internal recirculation of thickened sludge from the effluent and thermal-alkaline, thermal, and alkaline pre-treatment (7 days) were applied to the combined process. In phase 5, the raw sludge without any pre-treatment was used to the combined process. With the feed sludge pre-treatment and internal recirculation, the experimental results indicated that the volatile suspended solid (VSS) removal was drastically increased from phases 1 to 4. Also, the methane production rate with the thermal-alkaline pre-treatment and internal recirculation was significantly improved, showing an increment to 285 mL/L/day in phase 2. Meanwhile, the VSS removal and methane production in phase 5 were greatly decreased when the raw sludge without any pre-treatment was applied to the combined process. Considering all together, it was concluded that the combined process with the thickened sludge recirculation and thermal-alkaline pre-treatment can be successfully employed for the highly efficient sewage sludge reduction and methane gas production.

• Journal of Environmental Science International
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• v.15 no.7
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• pp.677-688
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• 2006

Currently, the application of $TiO_2$ photocatalyst has been focused on purification and treatment of wastewater. However, the use of conventional $TiO_2$ slurry photocatalyst results in disadvantage of stirring during the reaction and of separation after the reaction. And the usage of artificial UV lamp has made the cost of photocatalyst treatment system high. Consequently, we studied that solar light/$TiO_2$ film system was designed and developed in order to examine disinfection characteristics of sewage wastewater treatment. The optimum conditions for disinfection such as solar light intensity, characteristic of sewage wastewater, amounts of $TiO_2$ and comparison of solar ligth/$TiO_2$ systems with UV light/$TiO_2$ system was examined. The results are as follows: (1) photocatalytic disinfection process with solar light in the presence of $TiO_2$ film more effectively killed total coliform (TC) than solar light or $TiO_2$ film absorption only. (2) The survival ratio of TC and residual ratio of organic material (BOD, CODcr) decreased with remain resistant material. (3) The survival ratio of TC and residual ratio of organic material (BOD, CODcr) decreased with the increase of amounts of $TiO_2$. (4) TC survival ratio decreased linearly with increasing UV light intensity. (5) The disinfection effect of solar light/$TiO_2$ slurry system decreased more than UV light/$TiO_2$ film systems. (6) The disinfection reaction followed first-order kinetics. We suggest that solar light instead of using artificial UV light was conducted to investigate the applicability of alternative energy source in the disinfection of TC and the degradation of organic material.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1996.10a
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• pp.302-305
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• 1996

In this paper, an optimal identification method using fuzzy-neural networks is proposed for modeling of nonlinear complex systems. The proposed fuzzy-neural modeling implements system structure and parameter identification using the intelligent schemes together with optimization theory, linguistic fuzzy implication rules, and neural networks(NNs) from input and output data of processes. Inference type for this fuzzy-neural modeling is presented as simplified inference. To obtain optimal model, the learning rates and momentum coefficients of fuzz-neural networks(FNNs) and parameters of membership function are tuned using genetic algorithm(GAs). For the purpose of its application to nonlinear processes, data for route choice of traffic problems and those for activated sludge process of sewage treatment system are used for the purpose of evaluating the performance of the proposed fuzzy-neural network modeling. The show that the proposed method can produce the intelligence model w th higher accuracy than other works achieved previously.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.412-416
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• 1993

In this paper, fuzzy-neural network is proposed to identify the Activated Sludge Process(A.S.P) in sewage treatment such as "IF-THEN" type fuzzy rules and using various learning methods and improved complex method, the performance index of the identified model is improved. The proposed FNN has the neural network structure of which the connection weights have particular meanings for obtaining fuzzy inference rules and for tuning membership functions. And based on the identified model, graphic simulator which can analize nonlinear characteristics of A.S.P and generate control strategy for A.S.P is being developed.developed.

• Journal of Environmental Impact Assessment
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• v.22 no.6
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• pp.581-589
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• 2013

Generally, Sewage Treatment Plants(STPs) are complexes systems in which a range of physical, chemical and biological processes occur. However, their performance strongly depends on the know-how acquired by the field-engineer. Recently, in order to solve this situations, various operation and management technologies based on the Instrumentation, Control and Automation(ICA) have been developed. As a economies-environmental affect point of view, this study was for the performance evaluation and assessment of results from the Smart Operation System(SOS) in full-scale STP. The SOS in STP consisted of the process monitoring module, including real-time influent prediction and effluent simulation, and the Smart Air Control(SAC) module. According to the results from field test for 2 years, the results of economical evaluation, amount of benefits and cost saving by the SOS have shown to be much higher than that of traditional operation. Nevertheless, the removal load(kg/yr) of BOD 13.3 %, COD 28.2 %, TN 44.4 % and TP 20.8 % were increased, respectively. Remarkable improvement of removal load could be achieved after the SOS was adapted. It was concerned that the SOS offer a user friendly functionalities and cost saving needed by the field-engineers. In addition, it was expected that the results of this study would supply helpful information for design and cost saving for the SOS in full-scale STP.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.10a
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• pp.383-386
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• 1997

In this paper, We proposed a parallel structure of the Neural Network model to nonlinear complex system. Neural Network was used as basic model which has learning ability and high tolerence level. This paper, we used Neural Network which has BP(Error Back Propagation Algorithm) model. But it sometimes has difficulty to append characteristic of input data to nonlinear system. So that, I used HCM(hard c-Means) method of clustering technique to append property of input data. Clustering Algorithms are used extensively not only to organized categorize data, but are also useful for data compression and model construction. Gas furance, a sewage treatment process are used to evaluate the performance of the proposed model and then obtained higher accuracy than other previous medels.

• Applied Chemistry for Engineering
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• v.28 no.5
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• pp.581-586
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• 2017

In this study, in order to find the feasibility of thermophilic biological pre-treatment for the co-digestion of food wastewater and sewage sludge, digestion efficiency of the combined thermophilic aerobic and mesophilic anaerobic process and its effect on methane production were investigated. Also, a lab-scale co-digestion process was operated to observe parameter changes according to the increase of organic loading rates using different dilution ratios of distilled water and food wastewater (1/3 [Run I], 2/3 [Run II] in addition to using the raw food wastewater [Run III]). The results indicated that co-digestion process maintained quite stable and constant pH during entire experiments. With regard to VS removal, the higher removal was observed in the combined process and the removal efficiency was 52.24% (Run I), 66.59% (Run II) and 72.53 (Run III), respectively. In addition, the combined process showed about an 1.6-fold improved methane production rate and significantly higher methane yield than that of using single anaerobic digestion process.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.6
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• pp.43-52
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• 1994

A design method of rule-based fuzzy modeling is presented for the model identification of complex and nonlinear systems. The proposed rule-based fuzzy modeling implements system structure and parameter identification in the efficient form of ``IF....,THEN...', using the theories of optimization theory , linguistic fuzzy implication rules and fuzzy c-means clustering. Three kinds of method for fuzzy modeling presented in this paper include simplified inference (type I), linear inference (type 2), and modified linear inference (type 3). In order to identify premise structure and parameter of fuzzy implication rules, fuzzy c- means clustering and modified complex method are used respectively and the least sequare method is utilized for the identification of optimum consequence parameters. Time series data for gas furance and those for sewage treatment process are used to evaluate the performance of the proposed rule-based fuzzy modeling. Comparison shows that the proposed method can produce the fuzzy model with higher accuracy than previous other studies.