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Responses of fish assemblage structure to large-scale weir construction in riverine ecosystems
Jo, Hyunbin,Jeppesen, Erik,Ventura, Marc,Buchaca, Teresa,Gim, Jeong-Soo,Yoon, Ju-Duk,Kim, Dong-Hwan,Joo, Gea-Jae Elsevier 2019 The Science of the total environment Vol.657 No.-
<P><B>Abstract</B></P> <P>Worldwide, increasing amounts of dams and weirs have been established in rivers in recent decades, often with drastic effects on their ecosystems. Between late 2009 and 2011, 16 large-scale dams were built in the main channels of the four largest rivers in South Korea, eight of these along the main channel of Nakdong River (300 km, 520 km in total). We studied the effect of these constructions on the fish community in the riparian zone based on intensive fish field surveys conducted in the littoral zone during 2007–2017, analysis of fishermen's catch data and molecular analysis of the diet of the keystone species, largemouth bass (<I>Micropterus salmoides</I>). Our results, based on RDA and GLM analyses, showed that environmental characteristics and fish species composition changed significantly with dam construction. Total fish abundance and biomass decreased after the start of the weir construction and fish richness decreased with time. The abundance and biomass of exotic fish decreased during construction but recovered afterwards, leading to higher proportions of exotics. Dominance and Shannon indices did not change significantly from before to after construction, while the Evenness index showed a significant decreasing trend. A comparison of the diet composition of largemouth bass showed decreasing genetic variation after construction. The changes in Functional Feeding Group (FFG) of the benthic communities at the study sites did not coincide with FFG changes in the prey items of largemouth bass, indicating a transition in feeding mode from before to after construction. In conclusion, the endemic and native fish species were most sensitive and showed lower resilience to disturbance by the large-scale dam construction than the translocated and exotic species, and the lake-like ecosystems after construction markedly improved the competitive capacity of these exotic fish over the native and endemic species in the riparian zone of the river.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Native fish species were more sensitive to disturbance and showed low resilience. </LI> <LI> Shift in the feeding mode of largemouth bass from before to after weir construction </LI> <LI> Exotic fish had improved competitive capacity after weir construction. </LI> </UL> </P> <P><B>Graphical abstract</B></P> <P>[DISPLAY OMISSION]</P>
Jo, Hyunbin,Joo, Gea-Jae,Byeon, Myeoungseop,Hong, Dong-Gyun,Gim, Jung-Soo,Kim, Ji-Yoon,Choi, Jong-Yun The Ecological Society of Korea 2014 Journal of Ecology and Environment Vol.37 No.4
We conducted a distributional survey of Pectinatella magnifica, an invasive species, in the Geum River and the Nakdong River from July 12 to July 25, 2014. The spacing between the study sites was 10 km along the main channels for the Geum River (n = 12, 120 km) and the Nakdong River (n = 38, 380 km) from the estuarine barrage to upper part of main channel. Pectinatella magnifica was detected along the riparian zone (within 100 m) at each of the study sites. Presence rate of P. magnifica in Geum River and Nakdong River was 25% and 32.6%, respectively. The colony number of P. magnifica at Geum River ($9.5{\pm}3.1colony/m$, n = 3) was over 94 fold higher than that in the Nakdong River ($0.1{\pm}0.1colony/m$, n = 16). The Total length distribution of P. magnifica had a truncated bell shape at each rivers (mean length: $14.0{\pm}1.2cm$ for Geum River (n = 32), and $16.8{\pm}1.4cm$ for Nakdong River (n = 52)). These findings could provide basic information regarding the distribution pattern of P. magnifica in a new invasion area.
Hyunbin Jo,Kiseop Kang,Jong-Keun Park,Changkook Ryu,Hyunsoo Ahn,Younggun Go 대한기계학회 2020 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.34 No.2
Computational fluid dynamics (CFD) has become an essential tool for optimizing the design and diagnosing the operation of a boiler. However, the validity of the results depends on the degree of numerical diffusion as well as the reliability of the submodels. This study aims to assess mesh sensitivity in the reacting two-phase flow of pulverized coal in a common tangential-firing boiler. Three mesh versions were constructed for the boiler with the number of cells ranging between 1.2 million and 5.4 million, corresponding to 0.0114 -0.0022 m 3 per cell in the burner zone. The velocity distribution was found to be highly sensitive compared to temperature, heat flux, and NO concentration. By contrast, the use of key performance parameters such as total wall heat absorption, exit NOx concentration, and carbon conversion, was not appropriate criteria for the mesh sensitivity test. These parameters were determined by integration over the entire surface or volume, which made them sensitive to the overall reaction stoichiometry instead of the mesh fineness. It suggests that the use of a coarse mesh could be acceptable in evaluating the key performance parameters influenced by major operation variables, such as air distribution and fuel properties. However, sufficient mesh fineness is necessary for studies requiring accurate prediction of detailed flow patterns such as the evaluation of burner tilting/yawing or ash deposition on the wall.
딥러닝 기반 화력발전 보일러 출구 NOx 농도 선행 예측 모델
조현빈(Hyunbin Jo),강동협(Donghyup Kang),박성민(Seongmin Park),이종욱(Jongwuk Lee),류창국(Kang Y. Huh) 한국연소학회 2022 KOSCOSYMPOSIUM논문집 Vol.2022 No.11
In this study, we developed a deep learning model to forecast the NOx and oxygen concentration, and gas temperature at the boiler exit of a coal-fired power plant. The target boiler is a 500 MWe tangential firing boiler, which is one of 20 units often referred to as standard coal power plant. From the database of the power plant, 73 raw items of operation data with one-minute frequency were collected for a period of approximately 5 months. Through the feature selection procedure, the raw data items were condensed into 19 features which include coal feeder throughput to burners, air flow rate, and burner tilt. The features were then used to establish two types of data segments: segment #1 for current operation status and segment #2 for recent histories measured at the boiler exit. Considering the large fluctuations, the histories of the recent values at the boiler exit values were averaged over 5 min. After evaluating different prediction models with respect to the nature of the data segments, suitable models were applied in the form of ensemble model to forecast the boiler exit values 1 min in advance. When compared to measured data, the prediction quality was sufficiently high with a mean square error of 0.0123 for NOx emission.