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확률밀도함수 기반 유입하수 재현 및 활성슬러지공정 설계기법 개발
유광태 ( Kwangtae You ),김종락 ( Jongrack Kim ),윤주환 ( Zuhwan Yun ),박기정 ( Gijung Pakt ) 한국물환경학회 2017 한국물환경학회지 Vol.33 No.2
An important factor in determining the design and, therefore, the efficiency of wastewater treatment plants (WWTPs) is the influents` quantity and quality. Detailed and accurate information is essential for process control, diagnosis, and operation. In designing a plant, the optimal capacity of each bioreactor must be determined. Probabilistic models are used to predict the wastewater quantity and quality of WWTPs, which are widely used to improve plant designs and operations. In this study, the optimal probability distribution of time series data was derived to predict the influent`s water quantity and quality. Wastewater data were generated using a Monte Carlo simulation. In addition, we estimated various alternatives for the improvement of bioreactor operations based on present operation conditions, using the generated influent data and the activated sludge model, and suggested an alternative for an optimally effective plant operation. Since the influent quantity and quality were highly correlated with the actual operation data, the WWTPs` real influent characteristics were well reproduced. Adopting this suggested alternative will improve the operating conditions of WWTPs and an improvement plan for the current tele monitoring system`s effluent quality standards can be proposed.
토석류 모니터링 계측자료 신뢰도 향상을 위한 중앙값필터와 칼만필터 적용
김종락(Kim, Jongrack),유광태(You, Kwangtae),장수현(Jang, Suhyun),박기정(Pak, Gijung),이득수(Pak, Gijung) 한국방재학회 2017 한국방재학회논문집 Vol.17 No.1
원격 모니터링 시스템에서 계측되는 자료는 다양한 요인에 의해 이상값 및 잡음을 포함하게 된다. 정확한 분석을 위해서는 계측자료의 신뢰도가 매우 중요하다. 본 연구에서는 계측자료의 신뢰도 확보를 위해 이상값 제거에 개선된 중앙값 필터 알고리즘, 잡음 제거에 칼만필터 알고리즘을 함께 사용할 것을 제안하였다. 제안한 알고리즘을 현장 계측 자료에 적용한 결과, 잡음과 이상값을 모두 제거하였으며, 채널당 연산 시간이 1밀리초 이하로 매우 빨라 저사양 계측모듈에 쉽게 적용 가능함을 확인하였다. The data measured in the remote monitoring system will contain outlier values and noise due to various factors. Reliability of measured data is important for accurate analysis. In this study, we propose the use of an improved median filtering algorithm to remove outlier data, and Kalman filter algorithm to remove noise. After applying to the field measurement data, the proposed algorithm removed both outlier values and noise, and it was confirmed that the calculation time per channel was significantly low, at less than 1 millisecond, thus it can be easily applied to the low measurement module.
퍼지함수와 PDA 모형을 이용한 비상시 용수공급 성능지표 개발
옥수연(Oak Sueyeun),유광태(You Kwangtae),노헌승(Noh HunSeung),전환돈(Jun Hwandon) 한국방재학회 2018 한국방재학회논문집 Vol.18 No.2
The water distribution system is an infrastructure system supplying water to urban areas. Since it has a great influence on the quality of life and financial aspect of customers, the performance evaluation of the system for an efficient management and operation is essential. Until now, most of the suggested performance indicators for the system are based on the available demand and pressure at demand nodes obtained from the hydraulic simulation. However, those performance indicators based on the hydraulic simulation may not consider the actual usability of water for customers properly. Therefore, in this study, the application of fuzzy functions along with the available demands at demand nodes, which are obtained from the hydraulic simulation, from the various points of view, makes us possible to evaluate the system performance by depending on the set value of the variables. For this purpose, we use a PDA model, which can simulate various abnormal operation conditions and suggest two performance indicators: the possible water supply range indicator (PWSRI) for the water supply performance evaluation for an individual demand node and the possible water supply indicator for the entire system (PWSIES). The suggested method and indicators are applied to the real water distribution system of A-city in Korea to verify the applicability.Q 상수관망 시스템은 국내 전역에 용수를 공급해주는 사회기반시설로, 수요자의 삶의 질과 경제에 직접적인 영향을 끼치는 중요한 시스템으로 효율적인 관리와 운영을 위한 성능 평가가 필수적이다. 기존에 제안된 상수관망의 성능 평가를 위한 지표는 수리학적 해석을 통해 계산된 절점의 공급가능 유량 및 압력을 기반으로 한다. 그러나, 이와 같은 공급가능유량을 위주로 한 수리학적 성능 평가지표는 실제 수요자가 느끼는 용수의 사용성에 미치는 영향을 고려하기 힘들다. 따라 본 연구에서는 수리학적 해석을 통한 절점별 공급 가능 유량에 퍼지함수를 적용하여, 변수 조합에 따라 따양한 관점에서 공급 성능을 평가할 수 있는 새로운 공급 성능 지표를 제안하였다. 이를 위하여 다양한 비정상상황을 모의할 수 있는 PDA 수리해석 모형을 이용하여, 개별 절점의 공급 성능 평가를 위한 공급 범위 기준 성능 지표(PWSRI)와 전체 관망의 공급 성능을 평가할 수 있는 공급 가능량 기준 성능 지표(PWSIES)를 제안하였다. 또한 제안된 성능 지표들을 A시의 관망의 배수지 문제발생 시나리오에 적용하여 그 사용성을 검증하였다.
하수처리공정 모의시간 단축을 위한 개선된 뉴턴-랩슨 방법 개발 및 평가
김종락(Kim, Jongrack),유광태(You, Kwangtae),표우원화(Piao, Wenhua),김예진(Kim, Yejin) 한국방재학회 2018 한국방재학회논문집 Vol.18 No.5
유입수질 변동은 하수처리공정의 성능을 좌우하는 대표적 외란으로, 유입수질 변동에 따른 공정의 최적운전을 위해서는 공정 제어의 적용이나 최적운전방안 도출을 위한 공정 모의가 필수적이다. 공정 모의를 위해 현재 전 세계적으로 널리 사용되는 질소·인 제거공정 모델에는 IWA의 ASM2d 모델이 있고, 바이오가스 생산공정의 모의를 위해서는 ADM1 모델이 사용되며, 이들 모델은 상미분방정식으로 이루어져 있다. 하나의 하수처리장을 모의하는 데 있어 주어진 일련의 외란 조건과 운전 조건 하에서 공정의 정상상태를 모사하는 단계는 필수적인데, 이 때 상미분방정식를 해석하는 단계에서 연산시간이 오래 걸리는 단점이 존재한다. 연산시간을 단축하기 위해 본 연구에서는 상미분방정식 해석과 뉴턴-랩슨 알고리즘을 결합한 개선된 뉴턴-랩슨 방법을 제안하였다. 제안된 방법으로 공정을 모의한 결과, 상미분방정식 해석만을 적용하는 것과 비교할 때 ASM2d는 32.3배, ADM1은 8배 빠른 속도로 연산을 수행할 수 있었다. In order to optimize the process operation against fluctuating influent water quality, it is essential to apply process control and simulate the process for deriving the optimal operation method. To simulate the process, the ASM2d model and ADM model of the IWA have been widely used for the simulation of the nitrogen and phosphorus removal process and biogas production process, which consist of ordinary differential equations. In order to simulate a sewage treatment plant, it is essential to simulate the steady state of a process under a given set of disturbances and operating conditions. However, the disadvantage is that the calculation time is long when analyzing the ordinary differential equations. In order to shorten the computation time, we propose an improved Newton-Raphson method. As a result, the ASM2d and the ADM1 were able to simulate the processes 32.3 times and 8 times faster than ordinary differential equation analysis, respectively.
딥러닝 사물 인식 알고리즘(YOLOv3)을 이용한 미세조류 인식 연구
박정수 ( Jungsu Park ),백지원 ( Jiwon Baek ),유광태 ( Kwangtae You ),남승원 ( Seung Won Nam ),김종락 ( Jongrack Kim ) 한국물환경학회 2021 한국물환경학회지 Vol.37 No.4
Algal bloom is an important issue in maintaining the safety of the drinking water supply system. Fast detection and classification of algae images are essential for the management of algal blooms. Conventional visual identification using a microscope is a labor-intensive and time-consuming method that often requires several hours to several days in order to obtain analysis results from field water samples. In recent decades, various deep learning algorithms have been developed and widely used in object detection studies. YOLO is a state-of-the-art deep learning algorithm. In this study the third version of the YOLO algorithm, namely, YOLOv3, was used to develop an algae image detection model. YOLOv3 is one of the most representative one-stage object detection algorithms with faster inference time, which is an important benefit of YOLO. A total of 1,114 algae images for 30 genera collected by microscope were used to develop the YOLOv3 algae image detection model. The algae images were divided into four groups with five, 10, 20, and 30 genera for training and testing the model. The mean average precision (mAP) was 81, 70, 52, and 41 for data sets with five, 10, 20, and 30 genera, respectively. The precision was higher than 0.8 for all four image groups. These results show the practical applicability of the deep learning algorithm, YOLOv3, for algae image detection.
김종락 ( Jongrack Kim ),이가희 ( Gahee Rhee ),유광태 ( Kwangtae You ),김동윤 ( Dongyoun Kim ),이호식 ( Hosik Lee ) 한국물환경학회 2020 한국물환경학회지 Vol.36 No.6
This study aims to conserve and monitor energy use in public sewage treatment plants by utilizing data from the SCADA system and by controlling the aeration rate required for maintaining effluent water quality. Power consumption in the sewage treatment process was predicted using the equipment’s uptime, efficiency, and inherent power consumption. The predicted energy consumption was calibrated by measured data. Additionally, energy efficiency indicators were proposed based on statistical data for energy use, capacity, and effluent quality. In one case study, a sewage treatment plant operated via the SBR process used∼30% of energy consumed in maintaining the bioreactors and treated water tanks (included decanting pump and cleaning systems). Energy consumption analysis with the K-ECO Tool-kit was conducted for unit processing. The results showed that about 58.7% of total energy consumed was used in the preliminary and biological treatment rotating equipment such as the blower and pump. In addition, the energy consumption rate was higher to the order of 19.2% in the phosphorus removal process, 16.0% during sludge treatment, and 6.1% during disinfection and discharge. In terms of equipment energy usage, feeding and decanting pumps accounted for 40% of total energy consumed following 27% for blowers. By controlling the aeration rate based on the proposed feedback control system, the DO concentration was reduced by 56% compared pre-controls and the aeration amount decreased by 28%. The overall power consumption of the plant was reduced by 6% via aeration control.