Pilot-scale experimental study and Machine-learning Modeling application on Side-Stream EBPR (S2EBPR) by adaptation of operational factors

? Comprehensive review of S2EBPR, with a focus on operation, performance and microbial structure
? Evaluate and understand the effect of operational factors on conventional and S2EBPR systems by water quality monitoring, carbon, phosphorus and nitrogen mass balance, metabolic activity and kinetic tests and microbial ecology analysis
? Design and optimization of an S2EBPR system with considering the underlying fundamental mechanisms leading the performance including hydrolysis and fermentation steps in VFA generation
o Development and construction of a machine-learning based model to highly incorporate various aspects of process operation
o Prediction of S2EBPR process performance through a validated model
o Investigate and compare microbial community structures, process rates and kinetics in conventional EBPR and S2EBPR systems.

Intern: 
Parnian Izadi
Faculty Supervisor: 
Ahmed Eldyasti
Province: 
Ontario
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Partner University: 
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