An analytical method is proposed to predict the thermal conductivity of nanofluids by use of the macroscopic statistical characteristics of particle clustering suspensions. The algorithm is much simpler and more convenient than the fractal model method suggested and reported before. It is shown with numerical calculation and discussion that reliable predictions of the thermal conductivity for a nanofluid can be reached with the method presented in this paper. The physical meaning and practical prospects in the research and development for screening and optimizing nanofluids as new advanced working fluids are presented.
As is often assumed, rapid mix effectively distributes the dosed coagulant in suspension to promote subsequent flocculation of suspended particles and coagulant molecules. This study determined that the role of rapid mix is considerably more complex than conventionally assumed. Particles in the raw water samples from the Banxing Water Works of Taipei City were coagulated at high shear environment, during which flocs of size 40-70 lm were produced. The produced floc interior was compacted, and residual turbidity and the amount of dissolved natural organic matter (NOM) in suspension were substantially reduced. The subsequent stage of rapid mix slightly reduces floc size, further compacts the floc interior, and expels fine particles and some adsorbed NOM from the flocs. A sudden reduction in shearing rate produced large sized flocs with not so compact structures. Moreover, this action released fine particles from flocs into the suspension and enhanced adsorption of NOM onto solid surfaces.
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