Evidence map›Paper›PMID 39634401›Full record

ArticleHeliyon2024

Numerical study on inter-particle effects for multiple reacting biomass and coal particles based on Micro-CT morphology.

Dongyu Liang

Abstract read
In one paragraph

Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

1 author.

Dongyu LiangA. Leon Linton Department of Mechanical, Robotics and Industrial Engineering, Lawrence Technological University, Southfield, MI, 48075, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Co-firing of biomass with coal combines the environmental benefits of renewable biomass with the high energy content of coal. Although the common numerical simulation treats the biomass and coal particles with ideal morphology, real particles often demonstrate nonsmoothed surface and irregular shape. To understand the impact of particle morphology in a group of biomass and coal particles co-firing together and to inform simple models appropriate, this study investigated the interparticle effects among particles using realistic particle morphology, focusing on fluid dynamics such as temperature distribution, flow patterns and drag coefficients. Particle-scale computational fluid dynamics (CFD) simulations using micro-CT imaging showed that realistic particle shapes resulted in nonuniform flow fields and temperature distributions with different reaction intensities due to the species transportation. It is in contrast to traditional ideal shape models, which often rely on simplified spherical representations of particles and cannot capture the intricacies of real particle shapes. Realistic models revealed more complex surfaces, highly irregular particle structures, and varied reaction zones that affected the overall dynamics. In addition, changing the orientation of one particle affects the combustion characteristics of neighboring particles. This effect is also not captured while using the spherical structure. These differences underscore the critical impact of particle morphology on drag and heat transfer, thereby challenging conventional spherical models. The findings of this study advocate for a paradigm shift in CFD modeling approaches, emphasizing the importance of realistic particle representation to improve the accuracy of predictions and enhance the co-firing system efficiency.

Indexed as

BiomassCoalCo-firingGroup effectsMorphology

Identifiers

PMID39634401
PMCPMC11615495

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.