Hydrodynamic behavior of non-spherical particles in confined vertical flows: A resolved computational fluid dynamics-discrete element method study

We investigate the sedimentation and vertical hydraulic transport of non-spherical polymetallic nodules (PMNs) using the resolved computational fluid dynamics-discrete element method with multisphere particles spanning 98<Rep<2904. Shape effects induce 1.8–2.0 times drag enhancement relative to volume-equivalent spheres, arising from 50% larger frontal areas and wake asymmetry, reducing terminal velocities by 27%–29%. Vertical transport exhibits velocity-driven transitions from intermittent settling to stable convection, as demonstrated by residence time and drag force statistics. While PMNs exhibit enhanced rotational–translational coupling and broader force fluctuations, the regime progression qualitatively resembles that of volume-equivalent spherical particles. Drag variance evolution reveals contrasting behavior: small particles (d/D=0.082) show narrow distributions and wake suppression at higher velocities, while large particles (d/D=0.22) exhibit non-monotonic variance. These findings elucidate shape-confinement interactions in vertical transport and establish bounds on the applicability of volume-equivalent spherical particles in reduced-order models.

Authors

Institutions

Publication Details

Journal
Physics of Fluids
Published
2026-07-01
DOI
https://doi.org/10.1063/5.0330997
Primary Topic
Micro and Nano Robotics
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Hydrodynamic behavior of non-spherical particles in confined vertical flows: A resolved computational fluid dynamics-discrete element method study

Gopkumar Kuttikrishnan, Ratna Kumar Annabattula, Sujith Reddy Jaggannagari, Shakti Swaroop Choudhury et al.
Physics of Fluids
Micro and Nano Robotics
article

Hydrodynamic behavior of non-spherical particles in confined vertical flows: A resolved computational fluid dynamics-discrete element method study

Gopkumar Kuttikrishnan, Ratna Kumar Annabattula, Sujith Reddy Jaggannagari, Shakti Swaroop Choudhury, Amiya Prakash Das, Amudha Krishnan, Balaji Ramakrishnan
article en

Abstract

We investigate the sedimentation and vertical hydraulic transport of non-spherical polymetallic nodules (PMNs) using the resolved computational fluid dynamics-discrete element method with multisphere particles spanning 98<Rep<2904. Shape effects induce 1.8–2.0 times drag enhancement relative to volume-equivalent spheres, arising from 50% larger frontal areas and wake asymmetry, reducing terminal velocities by 27%–29%. Vertical transport exhibits velocity-driven transitions from intermittent settling to stable convection, as demonstrated by residence time and drag force statistics. While PMNs exhibit enhanced rotational–translational coupling and broader force fluctuations, the regime progression qualitatively resembles that of volume-equivalent spherical particles. Drag variance evolution reveals contrasting behavior: small particles (d/D=0.082) show narrow distributions and wake suppression at higher velocities, while large particles (d/D=0.22) exhibit non-monotonic variance. These findings elucidate shape-confinement interactions in vertical transport and establish bounds on the applicability of volume-equivalent spherical particles in reduced-order models.

Physics of FluidsVol. 38(7)
Indian Institute of Technology Madras (IN), National Institute of Ocean Technology (IN)
National Institute of Ocean Technology, Ministry of Earth Sciences
Openalex Percentile: Top 10%
Micro and Nano Robotics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.