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Effect of particle size in depth filtration: Measurements and modeling

Balasubramaniam Vigneswaran, University of Massachusetts Amherst


Depth filtration consists of four major phases: clean bed removal, filter ripening, steady state removal and breakthrough. Ripening is a consequence of previously captured particles serving as additional collectors, and is followed by a relatively steady state high quality water production. As particles deposit in a filter, pressure drop (headloss) across the filter increases. Particle removal and filter headloss characteristics vary with the size of particles in the filter influent. The transient behavior of a depth filter, as a function of particle size and system chemistry, was investigated by experimental and mathematical approaches in this work. Laboratory scale filtration experiments were conducted with coagulated monodisperse suspensions of six different size particles under controlled conditions. Two coagulants, a cationic salt and a cationic polyelectrolyte, were used for particle destabilization. Particle concentration in the filtrate and headloss across the filter bed were recorded. Based on the O'Melia and Ali model (1978) a semi-empirical mathematical model for particle removal was proposed. It was assumed that removal is proportional to the available deposition sites in the filter. Empirical models for headloss were presented. A hypothesis that the filter headloss is proportional to the volume of the deposit was also tested. Experimental results indicated that the volume of the deposit is the key factor in depth filtration for describing headloss and steady state removal characteristics. Smaller particles form high volume deposits. Compared to cationic salt, cationic polymer creates deposits with higher volume. Headloss increases while the rate of particle removal decreases with increasing deposit volume. The mathematical model presented in this work described the observed filter behavior well. Calibrated models using experimental data successfully predicted previously reported filter data under similar conditions. The effects of the size of particles on filter performance could be conceptualized well by the fractal dimension of the deposit aggregates. The effect of particle - particle interaction on the fractal dimension, which is a function of particle size and system chemistry, merits further research.

Subject Area

Environmental engineering|Chemical engineering

Recommended Citation

Vigneswaran, Balasubramaniam, "Effect of particle size in depth filtration: Measurements and modeling" (1997). Doctoral Dissertations Available from Proquest. AAI9737593.