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Open AccessJournal Article

Simulink Application On Dynamic Modeling Of Biological Waste Water Treatment For Aerator Tank Case

Alban Kuriqi
- 25 Nov 2014 - 
- Vol. 3, Iss: 11, pp 69-72
TLDR
In this article, Simulink modeling on Matlab is developed based on aerator tank model, which consists on movement of particles settled on bottom of the tank, by using air bubbling process.

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Citations
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Sustainable management of landfill leachate concentrate through recovering humic substance as liquid fertilizer by loose nanofiltration

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Evaluation of climate change impact on groundwater from semi-arid environment (Essaouira Basin, Morocco) using integrated approaches

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Understanding the role of extracellular polymeric substances in the rheological properties of aerobic granular sludge

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Current status and future prospects of sewer biofilms: Their structure, influencing factors, and substance transformations.

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References
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Activated sludge models ASM1, ASM2, ASM2d and ASM3 (in Japaneese)

TL;DR: A complete overview of the Activated Sludge Model (ASM) family can be found in this article, where the authors present ASM1, ASM2 and ASM3 together for the first time.
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Activated sludge wastewater treatment plant modelling and simulation: state of the art

TL;DR: These are the nowadays most frequently used white-box models for description of biological nitrogen and phosphorus removal activated sludge processes, mainly applicable to municipal wastewater systems, but can be adapted easily to specific situations such as the presence of industrial wastewater.
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WEST: modelling biological wastewater treatment

TL;DR: WEST is a general modelling and simulation environment and can, together with a model base, be used for this task, and the model base presented here is specific for biological wastewater treatment and is written in MSL-USER.
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Implementing ADM1 for plant-wide benchmark simulations in Matlab/Simulink

TL;DR: The experiences gained from a Matlab/Simulink implementation of ADM1 into the extended COST/IWA Benchmark Simulation Model (BSM2) are presented and the main conclusion is that if implemented properly, the ADm1 will also produce high-quality results in dynamic plant-wide simulations including noise, discrete sub-systems, etc. without imposing any major restrictions due to extensive computational efforts.