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|Title:||Dynamic simulation of granular filtration||Authors:||Tan, Li Liang||Keywords:||DRNTU::Engineering::Environmental engineering::Water treatment||Issue Date:||2016||Abstract:||Filtration has been the research subject for many years, yet there is still a lack of established and dynamic applicable models which could describe the complex mechanisms governing the clogging of filter columns. Clogged bed equations developed by far were entirely empirical, and the clogged bed circumstance was not fully apprehended. Through literature studies, it was also concurred that minimal studies has been done to evaluate the clogging of filter grains using Computational Fluid Dynamic (CFD) modules. To bridge the research gap, a comprehensive study of the clogging of filter column was carried out. This study serves to achieve 2 objectives: i) to design a numerical model which could predict closely the change in specific deposit and head loss incurred in a filter column throughout the filtration stage. The model could then be employed as a tool to estimate the maximum run length of the filter column, and ii) to demonstrate that CFD software can serve as an accelerated approach to comprehend the clogging mechanism of a filter column. For the first objective, theoretical and empirical equations were included in the development of a MATLAB model which allows the close prediction of the filter performance parameters as filtration progresses. The predicted time to limiting head obtained using the MATLAB model deviates slightly from the run length of a pilot-scale filter by 0% to 3.2%. For the second objective, more than 50 domains representing different clogging conditions were integrated into a CFD software. The simulated values for head loss deviates slightly from theoretical equations by 0% to 10% and was found to reside between the head loss values calculated using 2 empirical equations. In addition, methods to optimize the quality of mesh elements in the CFD software are proposed. Further works on enhancing the performance of the MATLAB model through the incorporation of an automatic iterative process are suggested. The CFD model could also be improved by minimizing the gap size near the domain walls.||URI:||http://hdl.handle.net/10356/67623||Rights:||Nanyang Technological University||Fulltext Permission:||restricted||Fulltext Availability:||With Fulltext|
|Appears in Collections:||CEE Student Reports (FYP/IA/PA/PI)|
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