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Numerical simulation study of gas-solid two-phase flow characteristics in borehole sampling of coal cuttings
Numerical simulation study of gas-solid two-phase flow characteristics in borehole sampling of coal cuttings
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Numerical simulation study of gas-solid two-phase flow characteristics in borehole sampling of coal cuttings
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Numerical simulation study of gas-solid two-phase flow characteristics in borehole sampling of coal cuttings
Numerical simulation study of gas-solid two-phase flow characteristics in borehole sampling of coal cuttings
Journal Article

Numerical simulation study of gas-solid two-phase flow characteristics in borehole sampling of coal cuttings

2025
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Overview
During the process of coal sampling through drilling and determining the gas content, the movement characteristics of coal particles within the borehole will affect the exposure time of the collected coal samples. Therefore, studying the movement characteristics of coal particles within the borehole is of great significance. This study employs CFD-DEM to simulate the transport dynamics of Rosin-Rammler distributed coal cuttings during pneumatic sampling, quantifying the effects of drill rod rotation (0-200 rpm) and particle size. Key findings reveal: (1) Axial migration velocity increases significantly with rotational speed, with 0.5-1 mm fine particles accelerating by 39% to 3.9 m s-1 at 100 rpm compared to static condition, though an optimal threshold exists at 150 rpm; (2) Rod rotation induces vortical flow fields, where bit geometry impedes coarse particles (>1 mm) in blade zones, while 0.5-1 mm particles migrate at velocities higher than 2-3 mm fractions under different rotational speeds; (3) Mass flow rate at the orifice doubles with speed (reaching 0.06 kg s-1 at 200 rpm), while static condition reduces efficiency by 50%. The observed significant velocity differentiation depending on particle size implies that using narrowly graded samples (e.g., obtained with adjacent sieve sizes such as 3-4 mm) could potentially improve the accuracy of lost gas content estimation by minimizing variations in particle transport history.