Evidence map›Paper›PMID 40248005›Full record

ArticleFrontiers in artificial intelligence2025

Optimized design and performance evaluation of long-pressure-short-extraction ventilation and dust removal system based on the Coanda effect.

Xinguo Wang, Jinbo Zhao, Yufu Li, Zhibin Li

Abstract read
In one paragraph

Article in Frontiers in artificial intelligence, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

4 authors.

Xinguo WangShangwan Coal Mine, Ordos, China.
Jinbo ZhaoShangwan Coal Mine, Ordos, China.
Yufu LiShangwan Coal Mine, Ordos, China.
Zhibin LiCCTEG Xi'an Research Institute Co. Ltd., Xi'an, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mine ventilation and dust control systems are crucial for ensuring occupational safety and health during underground mining operations. Traditional long-pressure short-suction systems face challenges such as inefficient airflow organization, formation of vortex dead zones, high energy consumption, and inadequate adaptability to dynamic conditions in mining faces. This study addresses these limitations by proposing an optimized long-pressure short-suction ventilation and dust control system leveraging the Coandă effect. Through numerical simulations, experimental validation, and machine learning techniques, the study develops a comprehensive system to enhance dust control performance. The Coandă effect was employed to optimize the structural design of ventilation ducts, ensuring airflow attachment to tunnel surfaces, reducing dust dispersion, and achieving high-efficiency airflow with lower power consumption. The key parameters optimized include the spacing between the air supply and exhaust ducts, the pressure-to-suction ratio, and the height of the ventilation duct. The optimal pressure-to-suction ratio was found to be 2:3, which minimizes dust concentration at both the mining machine and downstream locations. Numerical simulations and experimental results demonstrated that the optimized system achieved dust concentration reductions of up to 84.12% in high initial dust conditions (800 mg/m

Indexed as

CNN-LSTMCoandă effectdust controlmine ventilationpressure-to-suction ratio

Identifiers

PMID40248005
PMCPMC12004412

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.