Investigations on the Effect of Design Parameters on the Velocity Distribution in Swirling Fluidized Bed: An Experimental Study

Swirling fluidized bed machining (FBM) is a non-traditional method of abrasive machining which is a variant of FBM and finds its application in the polishing of surfaces with complex geometry with passages and grooves. Current research focus up on computational fluid dynamics (CFD) analysis by varying design parameters to identify their effect on velocity distribution and pressure drop across the air distributer. Various design parameters considered for CFD analysis using SOLID WORKS software are distributer hole diameter, distributer hole inclination, plenum chamber depth and air-inlet velocity. The simulation results in the form of charts, tables, graphs, images and animations emphasize that the optimized values of design parameters chosen for CFD have shown almost the same value of maximum velocity and same pattern in the velocity distribution across the cylindrical container. An experiment was also conducted to validate the optimized design parameters. Both the experimental as well as theoretical analysis results confirmed that maximum value of jet velocity with uniform pattern, encompass a region 10–170 mm from the distributer position across the cylindrical container. This region is identified as the region of maximum abrasive – metal interaction during SFM, which will result in fastest and effective surface modification.

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Publication Details

Journal
Premier journal of science.
Published
2026-02-03
DOI
https://doi.org/10.70389/pjs.100254
Primary Topic
Advanced Surface Polishing Techniques
Type
article
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article

Investigations on the Effect of Design Parameters on the Velocity Distribution in Swirling Fluidized Bed: An Experimental Study

Vishal John Mathai, S. Christopher Ezhil Singh, Jerril Gilda Sreedharan, Sridharan Ponnusamy et al.
Premier journal of science.
Advanced Surface Polishing Techniques
article

Investigations on the Effect of Design Parameters on the Velocity Distribution in Swirling Fluidized Bed: An Experimental Study

Vishal John Mathai, S. Christopher Ezhil Singh, Jerril Gilda Sreedharan, Sridharan Ponnusamy, Mary Little Flower Thomas, Jaya Christiyan Kumaravelu Grace JesyBai, Jessy Kochumman, Glan Devadhas George
article en

Abstract

Swirling fluidized bed machining (FBM) is a non-traditional method of abrasive machining which is a variant of FBM and finds its application in the polishing of surfaces with complex geometry with passages and grooves. Current research focus up on computational fluid dynamics (CFD) analysis by varying design parameters to identify their effect on velocity distribution and pressure drop across the air distributer. Various design parameters considered for CFD analysis using SOLID WORKS software are distributer hole diameter, distributer hole inclination, plenum chamber depth and air-inlet velocity. The simulation results in the form of charts, tables, graphs, images and animations emphasize that the optimized values of design parameters chosen for CFD have shown almost the same value of maximum velocity and same pattern in the velocity distribution across the cylindrical container. An experiment was also conducted to validate the optimized design parameters. Both the experimental as well as theoretical analysis results confirmed that maximum value of jet velocity with uniform pattern, encompass a region 10–170 mm from the distributer position across the cylindrical container. This region is identified as the region of maximum abrasive – metal interaction during SFM, which will result in fastest and effective surface modification.

Premier journal of science.
Altran (France) (FR), Vignana Jyothi Institute of Management (IN), M S Ramaiah University of Applied Sciences (IN), Art Innovation (Netherlands) (NL), St Xavier’s College (IN)
Openalex Percentile: Top 54%
Advanced Surface Polishing Techniques
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Investigations on the Effect of Design Parameters on the Velocity Distribution in Swirling Fluidized Bed: An Experimental Study — Vishal John Mathai, S. Christopher Ezhil Singh, et al. · Premier journal of science. (2026) | TGRS Research Map | TGRS