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고율 혐기성 공정과 아질산-아탈질을 연계한 수산물가공폐수의 질소제거
최용범,강동구,박상성,엄기현,임재명,권재혁,Choi, Yong-Bum,Kang, Dong-Gu,Park, Sang-Sung,Eum, Ki-Hyun,Rim, Jay-Myung,Kwon, Jae-Hyouk 한국환경보건학회 2011 한국환경보건학회지 Vol.37 No.4
Objectives: Organic matter and nitrogen were removed using the EGSB process, a high-rate anaerobic process, in combination with a nitritation-denitritation process, in order to ensure the stable treatment of seafood processing wastewater. Methods: The upflow velocity of an EGGS reactor was operated at 10 m/hr for maximal organics removal efficiency. For removal of nitrogen from seafood processing wastewater a nitritation-denitriation process was applied Results: The efficiency of the EGSB process showed that it has an 80% or more organic matter (CODcr) removal efficiency with an HRT of six hours or more at influent loadings of 17.34 kgCOD/$m^3$/day or less. The methane product for TCODcr removal was 0.23-0.38 $m^3CH_4$/kgCODrem., which was similar to the theoretical generation of STP-state methane, 0.35 $m^3CH_4$/kgTCODrem. In the nitritation-denitritation process, the nitritation conversion rate to $NH_4^+$-N concentration was 82% to 87%, 72% to 81% and 64% to 69% when HRT was 24 hr, 21 hr and 18 hr, respectively. In the denitritation process, the ratio of SCOD consumption to NOx-N removal ranged from 2.347 to 2.587. It was 2.472 on average. Conclusions: The optimal HRT for stable processing of seafood processing wastewater is six hours or more. The ratio of nitrite to total NOx-N was 82% to 96%, which indicates that nitrite accounts for the largest portion of the product.
최용범,조희석,이창환,김영민 한국물리학회 2019 THE JOURNAL OF THE KOREAN PHYSICAL SOCIETY Vol.74 No.9
One of the main targets for ground-based gravitational wave (GW) detectors such as Advanced LIGO (Laser Interferometer Gravitational wave Observatory) and Virgo is coalescences of neutron star (NS) binaries. Even though a NS's macroscopic properties such as mass and radius have been obtained from electro-magnetic wave observations, its internal structure has been studied mainly by using theoretical approaches. However, with the advent of Advanced LIGO and Virgo, the tidal deformability of a NS, which depends on the internal structure of the NS, has been recently obtained from GW observations. Therefore, reducing the measurement error of tidal deformability as small as possible in the GW parameter estimation is important. In this study, we introduce a post-Newtonian (PN) gravitational waveform model in which the tidal deformability contribution appears from 5 PN order, and we use the Fisher matrix (FM) method to calculate parameter measurement errors. Because the FM is computed semi-analytically using the wave function, the measurement errors can be obtained much faster than those of practical parameter estimations based on Markov Chain Monte Carlo method. We investigate the measurement errors for mass and tidal deformability by applying the FM to the nonspinning TaylorF2 waveform model. We show that if the tidal deformability corrections are considered up to the 6 PN order, the measurement error for the dimensionless tidal deformability can be reduced to about $75 \%$ compared to that obtained by considering only the 5 PN order correction.
저항 점용접에서 인공신경회로망을 이용한 용융부 추정에 관한 연구
최용범,장희석,조형석 대한기계학회 1993 대한기계학회논문집 Vol.17 No.2
In resistance spot welding process, size of molten nuggest have been utilized to assess the integrity of the weld quality. However real-time monitoring of the nugget size is an extremely difficult problem. This paper describes the design of an artificial neural networks(ANN) estimator to predict the nugget size for on-line use of weld quality monitoring. The main task of the ANN estimator is to realize the mapping characteristics from the sampled dynamic resistance signal to the actual negget size through training. The structure of the ANN estimator including the number of hidden layers and nodes in a layer is determined by an estimation error analysis. A series of welding experiments are performed to assess the performance of the ANN estimator. The results are quite promissing in that real-time estimation of the invisible nugget size can be achieved by analyzing the dynamic resistance signal without any conventional destructive testing of welds.