Evidence map›Paper›PMID 37207251›Full record

ArticleParticuology2023

Computational Fluid Dynamics Simulations of Aerosol Behavior in a High Speed (Heubach) Rotating Drum Dustiness Tester.

Hongyu Chen, Milind A Jog, Leonid A Turkevich

Abstract read
In one paragraph

Article in Particuology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Dust resuspension from the splash of a falling powder: A numerical aerodynamic simulation of a pellet falling onto a powder monolayer.Aerosol science and technology : the journal of the American Association for Aerosol Research · 2025
    Article
  3. Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Hongyu ChenThermal-Fluids and Thermal Processing Lab, Mechanical & Materials Engineering, University of Cincinnati, Cincinnati, OH 45221-0072.
Milind A JogThermal-Fluids and Thermal Processing Lab, Mechanical & Materials Engineering, University of Cincinnati, Cincinnati, OH 45221-0072.
Leonid A TurkevichDivision of Field Studies and Engineering (DFSE), National Institute for Occupational Safety & Health (NIOSH), The Centers for Disease Control & Prevention (CDC), Alice Hamilton Laboratory, 1090 Tusculum Avenue, Cincinnati, OH 45226.

Funding

Intramural CDC HHS CC999999
6 · The paper itself

Abstract

Potential exposure from hazardous dusts may be assessed by evaluating the dustiness of the powders being handled. Dustiness is the tendency of a powder to aerosolize with a given input of energy. We have previously used computational fluid dynamics (CFD) to numerically investigate the flow inside the European Standard (EN15051) Rotating Drum dustiness tester during its operation. The present work extends those CFD studies to the widely used Heubach Rotating Drum. Air flow characteristics are investigated within the Abe-Kondoh-Nagano k-epsilon turbulence model; the aerosol is incorporated via a Euler-Lagrangian multiphase approach. The air flow inside these drums consists of a well-defined axial jet penetrating relatively quiescent air. The spreading of the Heubach jet results in a fraction of the jet recirculating as back-flow along the drum walls; at high rotation rates, the axial jet becomes unstable. This flow behavior qualitatively differs from the stable EN15051 flow pattern. The aerodynamic instability promotes efficient mixing within the Heubach drum, resulting in higher particle capture efficiencies for particle sizes

Indexed as

AKN k-epsilon TurbulenceDustinessEuler-Lagrangian MultiphaseRotating Drum

Identifiers

PMID37207251
PMCPMC10193456

What OpenQuestion holds

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Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.