Sedimentation, Mineralization and Resuspension of Sludge in a Sewerage System: A Case Study

1985 ◽  
Vol 17 (6-7) ◽  
pp. 1223-1231
Author(s):  
A. S. Hogendoorn-Roozemond
Keyword(s):  
Sewage Treatment ◽  
Sewage Treatment Plant ◽  
Treatment Plant ◽  
Weather Conditions ◽  
Quantitative Information ◽  
Weather Data ◽  
Organic Load ◽  
Sewerage System ◽  
System A

Quantitative information was obtained on the processes of sedimentation, mineralization and resuspension of organic matter in a combined sewerage system by means of statistical analysis of dry and wet weather data on sewage flows. The effects of temperature and length of intermittent dry weather periods on daily pollutant loads were also evaluated. For the sewerage system investigated it was found that in summer 5-26% of the BOD produced is mineralized in the system before reaching the sewage treatment plant. Due to sedimentation under dry weather conditions up to 12% of the daily organic load produced may be present in the sewers as resuspendable deposits; in winter this percentage may even amount to 20-30% because of slow mineralization.

Integrative Fuzzy Set Pair Model for Safety Pre-Evaluation in Construction Stage

2011 ◽  
Vol 94-96 ◽  
pp. 2325-2328
Author(s):  
Li Xin Li ◽  
Hong Zhen Li ◽  
Yu Bing Duan ◽  
Xu Wang
Keyword(s):  
Fuzzy Set ◽  
Sewage Treatment ◽  
Sewage Treatment Plant ◽  
Treatment Plant ◽  
Construction Stage ◽  
Pair Model ◽  
Hierarchy Analysis ◽  
Pair Analysis ◽  
Fuzzy Hierarchy

The integrative fuzzy set pair model, established by set pair analysis (SPA) and fuzzy hierarchy analysis, was introduced to pre-evaluation of security states in the construction stage. Two relevant sets, evaluation index and dangerous standard, were analyzed and calculated in terms of the identity, discrepancy and contradistinction[1]. The indices and weights were determined by Delphi and fuzzy hierarchy analysis respectively in order to establish the integrative fuzzy set pair model of construction stage. Finally, the model was applied to the case study of Shenyang sewage treatment plant and the results demonstrated that the method proposed in this present paper is satisfactory.

MPC of Sewage Treatment Process

2020 ◽  
Vol 3 (1) ◽  
Author(s):  
Jiahui Meng ◽  
Qingyuan Zhao ◽  
Yu Zhang ◽  
Guanglei Wen ◽  
Huimin Ge ◽  
...  
Keyword(s):  
Neural Network ◽  
Treatment Process ◽  
Sewage Treatment ◽  
Sewage Treatment Plant ◽  
Treatment Plant ◽  
Weather Conditions ◽  
Learning Ability ◽  
Control Effect ◽  
Control Goal ◽  
Control Layer

Sewage treatment is one of the main methods to promote the recycling of water resources. The control goal of sewage treatment process is to reduce energy consumption under the premise that the effluent quality reaches the standard. In recent years, model predictive control (MPC) has attracted some attention in sewage treatment. Neural network is widely used in control field because of its strong online learning ability. BP neural network is selected as the prediction layer and control layer of MPC and applied to sewage treatment plant to realize on-line control of dissolved oxygen and nitrate. The training index of traditional neural network usually only selects the error between measured value and set value as the variable, and now the change of control quantity is also taken as the training index variable of control layer to adjust the weight relation between them to get the best control effect. Considering that different weather conditions will have a greater impact on the water inflow, different coefficients of the two can be selected to achieve better results in different weather.

Multi-way modeling of wastewater data for performance evaluation of sewage treatment plant—A case study

2009 ◽  
Vol 95 (1) ◽  
pp. 18-30 ◽  
Author(s):  
Kunwar P. Singh ◽  
Nikita Basant ◽  
Amrita Malik ◽  
Sarita Sinha ◽  
Gunja Jain
Keyword(s):  
Performance Evaluation ◽  
Sewage Treatment ◽  
Sewage Treatment Plant ◽  
Treatment Plant
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