TY - JOUR
T1 - Particle-resolved direct numerical simulation of drag force on permeable, non-spherical aggregates
AU - Mola, Ismael A.
AU - Fawell, Phillip D.
AU - Small, Michael
PY - 2020/6/8
Y1 - 2020/6/8
N2 - Aggregation within particle suspensions is often sought to enhance settling. Aggregate settling velocity and density predictions are directly related to the drag coefficient. Despite extensive studies on aggregate drag forces, there remains a lack of explicit correlations suitable across a range of properties and flow conditions; most employ implicit approaches assuming non-spherical, porous aggregates are rigid spheres. Particle-resolved Direct Numerical Simulation (DNS) was used to directly study drag on aggregates with various properties (void fraction, shape, orientation, fractal dimension) for Reynolds numbers between 0.13 and 2256. Testing previous implicit models against DNS results, the smallest error achieved was ~21%. From simple modifications accounting for aggregate shape and orientation, three new implicit models are proposed that substantially improve drag prediction, reducing error to ~11%. Using DNS, a new explicit correlation is proposed to calculate drag coefficients for porous aggregates of arbitrary shape spanning a range of properties with only ~6% error.
AB - Aggregation within particle suspensions is often sought to enhance settling. Aggregate settling velocity and density predictions are directly related to the drag coefficient. Despite extensive studies on aggregate drag forces, there remains a lack of explicit correlations suitable across a range of properties and flow conditions; most employ implicit approaches assuming non-spherical, porous aggregates are rigid spheres. Particle-resolved Direct Numerical Simulation (DNS) was used to directly study drag on aggregates with various properties (void fraction, shape, orientation, fractal dimension) for Reynolds numbers between 0.13 and 2256. Testing previous implicit models against DNS results, the smallest error achieved was ~21%. From simple modifications accounting for aggregate shape and orientation, three new implicit models are proposed that substantially improve drag prediction, reducing error to ~11%. Using DNS, a new explicit correlation is proposed to calculate drag coefficients for porous aggregates of arbitrary shape spanning a range of properties with only ~6% error.
KW - Fractal aggregates
KW - Drag coefficient
KW - Non-spherical
KW - Direct numerical simulation
UR - http://www.scopus.com/inward/record.url?scp=85079618259&partnerID=8YFLogxK
U2 - 10.1016/j.ces.2020.115582
DO - 10.1016/j.ces.2020.115582
M3 - Article
AN - SCOPUS:85079618259
SN - 0009-2509
VL - 218
JO - Chemical Engineering Science
JF - Chemical Engineering Science
M1 - 115582
ER -