Effect of Cooling Water Quality on Dendrite Arm Spacing of DC Cast Billets

In the years from 1970-1982 52 site studies and monitoring studies have been carried out at major existing and planned power plants. The results from the studies have been used in a planning system for water quality. This planning system, which is water quality related, is described in this paper. An important part of the planning system is the description of size and distribution of excess temperature fields and the related biological conditions. In the biological monitoring, emphasis is placed on the benthic community as more vulnerable to the cooling water discharge. The studies have shown that the excess temperature field within the 1-2° isotherm can produce measurable changes in the benthic community. The temperature effect in the pelagic zone is marginal, however, some effects are seen at sites with a deep water intake of nutrient rich water. Entrainment of fish and Zooplankton can be important in bays and estuaries.

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Characterization and UV Treatment of Cooling Water from an Oil Refinery

International Journal of Sustainable Water and Environmental Systems ◽

10.5383/swes.7.02.006 ◽

2015 ◽

Vol 07 (2) ◽

Keyword(s):

Water Quality ◽

Organic Carbon ◽

Water Samples ◽

Uv Light ◽

Cooling Water ◽

Oxygen Demand ◽

Biological Oxygen Demand ◽

Oil Refinery ◽

Uv Treatment ◽

Uv Light Irradiation

The cooling water from a local oil refinery was sampled, analyzed and experimentally treated with UV light irradiation at a wavelength of ~254nm. Total Organic Carbon (TOC), Biological Oxygen Demand (BOD), Chemical Oxygen Demand (COD) and bacteria count (BC) were analyzed for the water samples over years to monitor the water quality. The experimental results showed that: 1) The cooling water quality (e.g. organic matters) varies significantly over the years’ operation, probably due to the change in weather (mainly the temperature); 2) The UV treatment was highly effective for the disinfection of cooling water. Within a 24 hour treatment period, it was observed that the bacteria count decreased from 3890 cfu/ml to practically undetectable, which is consistent with the UV/Vis analysis that the absorbance at 254 nm was decreased significantly over the time. The degradation of chemicals by UV was also observed in the experiment.

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Water Quality Analysis by Nakajima Diagram of Cooling-water System Copper Pitting Corrosion

Zairyo-to-Kankyo ◽

10.3323/jcorr.62.377 ◽

2013 ◽

Vol 62 (10) ◽

pp. 377-382 ◽

Cited By ~ 1

Author(s):

Hiroshi Nakajima

Keyword(s):

Water Quality ◽

Pitting Corrosion ◽

Water System ◽

Cooling Water ◽

Quality Analysis ◽

Water Quality Analysis ◽

Cooling Water System

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ON THE POSSIBILITY OF IMPROVING THE FLOW AND WATER QUALITY ENVIRONMENT IN A CLOSED INLAND BAY USING COOLING WATER FROM A POWER GENERATING PLANT

Advances in Fluid Modeling and Turbulence Measurements ◽

10.1142/9789812777591_0095 ◽

2002 ◽

Author(s):

MICHIHIRO SHIBAZAKI ◽

TAIRYU TAKANO ◽

AKIRA WADA

Keyword(s):

Water Quality ◽

Cooling Water

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Study on Monitoring Water Quality Stability of Cycle Cooling Water by Stability Index in Power Plant

Advances in Intelligent and Soft Computing - Proceedings of the 2011 International Conference on Informatics, Cybernetics, and Computer Engineering (ICCE2011) November 19–20, 2011, Melbourne, Australia ◽

10.1007/978-3-642-25194-8_88 ◽

2011 ◽

pp. 755-762 ◽

Cited By ~ 1

Author(s):

Mo-Jie Sun ◽

Ming Cheng ◽

Xiao-Qing Wang ◽

Chun-Guang Liu

Keyword(s):

Water Quality ◽

Power Plant ◽

Cooling Water ◽

Stability Index ◽

Quality Stability

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The Research of the Water Quality Prediction Model for the Circulating Cooling Water System

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.385-386.408 ◽

2013 ◽

Vol 385-386 ◽

pp. 408-411

Author(s):

Qiang Gao ◽

Tian Lu Ma ◽

Jun Fang Li ◽

Chen Guang Li

Keyword(s):

Neural Network ◽

Water Quality ◽

Prediction Model ◽

Bp Neural Network ◽

Water System ◽

Cooling Water ◽

Water Quality Prediction ◽

Network Training ◽

Prediction Function ◽

Circulating Cooling Water

Aiming at the common quality faults of scaling and corrosion in circulating cooling water, water quality index were often used to determine the scaling and corrosion of circulating cooling water quality trends. Prediction model of corrosion and scaling rate was built based on BP Neural Network in this paper. The optimal initial individuals were written into the network operating system to optimize the disadvantages of weights and thresholds in BP neural network based on genetic algorithm. The prediction function would output after the network training after comparison of predicted and actual values of the model. The performance of the actual situation was verified to match the model prediction.

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