EN06 computational environmental hydraulics : pre-treatment filter modeling
The objective of this Final Year Project is to improve an existing mathematical model, NEWRI HFM, which emulates the flow through a dual media rapid filtration system. The main improvement involves incorporating a particle size distribution for the particles present in the feed water. Different size...
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sg-ntu-dr.10356-606502023-03-03T17:15:10Z EN06 computational environmental hydraulics : pre-treatment filter modeling Krishnan Moorthi, Pavithra Law Wing-Keung, Adrian School of Civil and Environmental Engineering Nanyang Environment and Water Research Institute DRNTU::Engineering::Environmental engineering The objective of this Final Year Project is to improve an existing mathematical model, NEWRI HFM, which emulates the flow through a dual media rapid filtration system. The main improvement involves incorporating a particle size distribution for the particles present in the feed water. Different size particles are preferentially removed at different depths of the filter. It has been observed that while the removal of particles of larger sizes stops or is decreasing, the removal of particles of smaller sizes continues to increase. The particle size distribution hence becomes a function of the filter depth and time. Very limited literature is available in this field of study as majority of the early literature published assumes a homogeneous, average particle size. This improved model is therefore able to predict the filter performance more effectively by taking into consideration the particle size distribution of the influent water, and is also able to assess the effect of particle size distribution on headloss, sediment deposition and total suspended solids decay in the filter. The existing MatLab codes were edited to allow users to input the specific particle sizes present in the influent and their concentrations as a percentage of the total particle concentration of the influent. Input parameters were limited to four particle sizes with the same concentration values and the headloss was capped at an appropriate value. The results of the code were also analysed in this report. The headloss values have been plotted against time to analyze the impact of incorporating a particle size distribution on the time taken to reach the maximum headloss values and the trend of head loss progression in the filter. Sediment deposition profiles have also been generated to evaluate how the sediment deposition in the filter changes with a changing particle size distribution. Different particle sizes exhibit different deposit patterns at different layers in the dual media filter. Lastly, images of the total suspended solids decay in the filter had also been generated, and comparisons were made with the sediment deposition profiles to assess the correlations. The impact of the different particle size distributions on the total suspended solids decay has also been analyzed. Bachelor of Engineering (Environmental Engineering) 2014-05-29T03:44:24Z 2014-05-29T03:44:24Z 2014 2014 Final Year Project (FYP) http://hdl.handle.net/10356/60650 en Nanyang Technological University 74 p. application/pdf |
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DRNTU::Engineering::Environmental engineering Krishnan Moorthi, Pavithra EN06 computational environmental hydraulics : pre-treatment filter modeling |
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The objective of this Final Year Project is to improve an existing mathematical model, NEWRI HFM, which emulates the flow through a dual media rapid filtration system. The main improvement involves incorporating a particle size distribution for the particles present in the feed water. Different size particles are preferentially removed at different depths of the filter. It has been observed that while the removal of particles of larger sizes stops or is decreasing, the removal of particles of smaller sizes continues to increase. The particle size distribution hence becomes a function of the filter depth and time. Very limited literature is available in this field of study as majority of the early literature published assumes a homogeneous, average particle size. This improved model is therefore able to predict the filter performance more effectively by taking into consideration the particle size distribution of the influent water, and is also able to assess the effect of particle size distribution on headloss, sediment deposition and total suspended solids decay in the filter. The existing MatLab codes were edited to allow users to input the specific particle sizes present in the influent and their concentrations as a percentage of the total particle concentration of the influent. Input parameters were limited to four particle sizes with the same concentration values and the headloss was capped at an appropriate value. The results of the code were also analysed in this report. The headloss values have been plotted against time to analyze the impact of incorporating a particle size distribution on the time taken to reach the maximum headloss values and the trend of head loss progression in the filter. Sediment deposition profiles have also been generated to evaluate how the sediment deposition in the filter changes with a changing particle size distribution. Different particle sizes exhibit different deposit patterns at different layers in the dual media filter. Lastly, images of the total suspended solids decay in the filter had also been generated, and comparisons were made with the sediment deposition profiles to assess the correlations. The impact of the different particle size distributions on the total suspended solids decay has also been analyzed. |
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Law Wing-Keung, Adrian |
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Law Wing-Keung, Adrian Krishnan Moorthi, Pavithra |
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Final Year Project |
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Krishnan Moorthi, Pavithra |
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Krishnan Moorthi, Pavithra |
title |
EN06 computational environmental hydraulics : pre-treatment filter modeling |
title_short |
EN06 computational environmental hydraulics : pre-treatment filter modeling |
title_full |
EN06 computational environmental hydraulics : pre-treatment filter modeling |
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EN06 computational environmental hydraulics : pre-treatment filter modeling |
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EN06 computational environmental hydraulics : pre-treatment filter modeling |
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en06 computational environmental hydraulics : pre-treatment filter modeling |
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2014 |
url |
http://hdl.handle.net/10356/60650 |
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1759857687874502656 |