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Table · dataset · 2026

<p>Factor levels for the response surface design.</p>

Listed in figshare and Loughborough Research Repository — shown once because both records carry DOI 10.1371/journal.pone.0338763.t003

<div><p>At fully mechanized heading faces, dust accumulation in roadways poses persistent safety and occupational health risks, particularly under long-forcing, short-exhaust hybrid ventilation conditions, with the return-air-side corners being critical dust accumulation zones.

Description

This study aimed to optimize the ventilation system and reduce dust mass concentrations by combining numerical simulations with response surface methodology (RSM).

A simplified geometric model was developed in SpaceClaim, and numerical simulations were performed using ANSYS Fluent. Single-factor analysis and a Box--Behnken experimental design were employed to investigate the effects of the exhaust duct inlet angle, exhaust-to-forcing airflow ratio, exhaust duct inlet diameter, and forcing duct outlet diameter. The results showed that the exhaust duct inlet angle and diameter were the dominant factors affecting dust distribution.

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Through multi-objective optimization, the dust mass concentrations at the lower and upper return-air-side corners were reduced by 58% and 34%, respectively. Validation using a 1:4 scaled-model experimental platform showed that the experimental measurements agreed well with the numerical predictions, with relative errors below 5%. This study developed an integrated research framework combining numerical simulation, response surface optimization, and scaled-model experimental validation to address dust accumulation in the return-air-side corner regions under a long-forcing, short-exhaust hybrid ventilation system.

The proposed framework enables the coupled analysis of multiple ventilation parameters and the dual-objective optimization of dust mass concentrations at the upper and lower return-air-side corners, providing a reference for dust control and ventilation parameter optimization under similar operating conditions.</p></div>

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Inferred from text
Simulation 75%
Provenance · 2 source records, 34 field assertions
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figshareoai:figshare.com:article/339752059 d agoJSON v1
Loughborough Research Repositoryoai:figshare.com:article/339752059 d agoJSON v1
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