2026-10-12T05:41:59Z https://api.figshare.com/v2/oai

oai:figshare.com:article/33975205 2026-09-23T17:26:46Z category_146 category_7 category_39 category_734 category_133 portal_5 item_type_3 month_year_09_2026

<p>Factor levels for the response surface design.</p> Xiaokun Zhao (212561) Yuting Zhang (337082) Jun Ge (298545) Wencai Wang (1614409) Yuhua Bai (4261270) Donghui Yang (289640) Space Science Medicine Ecology Biological Sciences not elsewhere classified Plant Biology simplified geometric model roadhead mining based response surface methodology proposed framework enables occupational health risks 34 %, respectively multiple ventilation parameters response surface optimization model experimental validation dust mass concentrations ventilation parameter optimization side corner regions address dust accumulation combining numerical simulations forcing airflow ratio dust accumulation numerical simulations ventilation system objective optimization validation using dust control numerical predictions side corners xlink "> study aimed rsm ). results showed relative errors factor analysis coupled analysis 5 %. <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. 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. 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> 2026-09-23T17:26:25Z Dataset Dataset 10.1371/journal.pone.0338763.t003 https://figshare.com/articles/dataset/_p_Factor_levels_for_the_response_surface_design_p_/33975205 CC BY 4.0