Dimensionless Analysis of Rough Roadway Airflow Distribution Based on Numerical Simulations

As resources are extracted from the deeper sections of a mine, the ventilation network becomes increasingly complex. Consequently, determining the optimal installation location for speed-measuring equipment that accurately reflects the average wind speed along the roadway remains a challenging task....

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Main Authors: Zongcheng Jia, Qiang Zhao, Yan Zhao, Baoyu Cui, Tao Song
Format: Article
Language:English
Published: MDPI AG 2025-03-01
Series:Fluids
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Online Access:https://www.mdpi.com/2311-5521/10/4/77
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author Zongcheng Jia
Qiang Zhao
Yan Zhao
Baoyu Cui
Tao Song
author_facet Zongcheng Jia
Qiang Zhao
Yan Zhao
Baoyu Cui
Tao Song
author_sort Zongcheng Jia
collection DOAJ
description As resources are extracted from the deeper sections of a mine, the ventilation network becomes increasingly complex. Consequently, determining the optimal installation location for speed-measuring equipment that accurately reflects the average wind speed along the roadway remains a challenging task. In this study, two three-dimensional geometric models, smooth and rough, were developed based on field conditions. The cross-sectional widths, heights, and flow velocities of the model channels were processed dimensionlessly. The dimensionless velocity distributions of the smooth and rough models were then analyzed for different Reynolds numbers. It was observed that the dimensionless average velocity ring distributions for the rough model were smaller than those for the smooth model. Additionally, the maximum values of dimensionless flow velocities were negatively correlated with the flow velocities under laminar flow conditions, whereas they largely overlapped under turbulent flow. The dimensionless distances of the average velocity rings from the top and sidewalls of the channel were studied and determined for both models across different flow regimes. Specifically, the dimensionless distance values <inline-formula data-eusoft-scrollable-element="1"><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline" data-eusoft-scrollable-element="1"><semantics data-eusoft-scrollable-element="1"><mrow data-eusoft-scrollable-element="1"><mi data-eusoft-scrollable-element="1">d</mi><mtext data-eusoft-scrollable-element="1"> </mtext><mo data-eusoft-scrollable-element="1">(</mo><mo data-eusoft-scrollable-element="1">−</mo><mo data-eusoft-scrollable-element="1">)</mo></mrow></semantics></math></inline-formula> were found to be 0.111 for the smooth model and 0.101 for the rough model under the laminar regime. Under the turbulence regime, the corresponding values were 0.106 and 0.108. Likewise, the values of <inline-formula data-eusoft-scrollable-element="1"><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline" data-eusoft-scrollable-element="1"><semantics data-eusoft-scrollable-element="1"><mrow data-eusoft-scrollable-element="1"><mi data-eusoft-scrollable-element="1">h</mi><mtext data-eusoft-scrollable-element="1"> </mtext><mo data-eusoft-scrollable-element="1">(</mo><mo data-eusoft-scrollable-element="1">−</mo><mo data-eusoft-scrollable-element="1">)</mo></mrow></semantics></math></inline-formula> were 0.135 and 0.135 for the smooth and rough models in the laminar flow regime, while under turbulent flow, the values were 0.131 and 0.162, respectively. The largest dimensionless velocity value was identified at the center of the velocity distribution circle. For corners that did not maintain simple parallelism with the walls, these regions were incorporated into the circle equation using the Least Squares Method, providing a theoretical basis for the placement of velocity-measuring equipment in practical applications. By using the sidewall as the reference coordinate, an appropriate mathematical model was employed to establish the functional relationship between the centerline velocity of the roadway and the dimensionless horizontal coordinate. The fitting results showed good agreement, and this model can be used to back-calculate and expand the potential installation locations for a mine anemometer.
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spelling doaj-art-e97d6e4d222e436aa4e9197267d663bd2025-08-20T02:17:14ZengMDPI AGFluids2311-55212025-03-011047710.3390/fluids10040077Dimensionless Analysis of Rough Roadway Airflow Distribution Based on Numerical SimulationsZongcheng Jia0Qiang Zhao1Yan Zhao2Baoyu Cui3Tao Song4School of Resources & Civil Engineering, Northeastern University, Shenyang 110819, ChinaSchool of Resources & Civil Engineering, Northeastern University, Shenyang 110819, ChinaSchool of Resources & Civil Engineering, Northeastern University, Shenyang 110819, ChinaSchool of Resources & Civil Engineering, Northeastern University, Shenyang 110819, ChinaState Key Laboratory of Intelligent Optimized Manufacturing in Mining& Metallurgy Process, Beijing 100160, ChinaAs resources are extracted from the deeper sections of a mine, the ventilation network becomes increasingly complex. Consequently, determining the optimal installation location for speed-measuring equipment that accurately reflects the average wind speed along the roadway remains a challenging task. In this study, two three-dimensional geometric models, smooth and rough, were developed based on field conditions. The cross-sectional widths, heights, and flow velocities of the model channels were processed dimensionlessly. The dimensionless velocity distributions of the smooth and rough models were then analyzed for different Reynolds numbers. It was observed that the dimensionless average velocity ring distributions for the rough model were smaller than those for the smooth model. Additionally, the maximum values of dimensionless flow velocities were negatively correlated with the flow velocities under laminar flow conditions, whereas they largely overlapped under turbulent flow. The dimensionless distances of the average velocity rings from the top and sidewalls of the channel were studied and determined for both models across different flow regimes. Specifically, the dimensionless distance values <inline-formula data-eusoft-scrollable-element="1"><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline" data-eusoft-scrollable-element="1"><semantics data-eusoft-scrollable-element="1"><mrow data-eusoft-scrollable-element="1"><mi data-eusoft-scrollable-element="1">d</mi><mtext data-eusoft-scrollable-element="1"> </mtext><mo data-eusoft-scrollable-element="1">(</mo><mo data-eusoft-scrollable-element="1">−</mo><mo data-eusoft-scrollable-element="1">)</mo></mrow></semantics></math></inline-formula> were found to be 0.111 for the smooth model and 0.101 for the rough model under the laminar regime. Under the turbulence regime, the corresponding values were 0.106 and 0.108. Likewise, the values of <inline-formula data-eusoft-scrollable-element="1"><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline" data-eusoft-scrollable-element="1"><semantics data-eusoft-scrollable-element="1"><mrow data-eusoft-scrollable-element="1"><mi data-eusoft-scrollable-element="1">h</mi><mtext data-eusoft-scrollable-element="1"> </mtext><mo data-eusoft-scrollable-element="1">(</mo><mo data-eusoft-scrollable-element="1">−</mo><mo data-eusoft-scrollable-element="1">)</mo></mrow></semantics></math></inline-formula> were 0.135 and 0.135 for the smooth and rough models in the laminar flow regime, while under turbulent flow, the values were 0.131 and 0.162, respectively. The largest dimensionless velocity value was identified at the center of the velocity distribution circle. For corners that did not maintain simple parallelism with the walls, these regions were incorporated into the circle equation using the Least Squares Method, providing a theoretical basis for the placement of velocity-measuring equipment in practical applications. By using the sidewall as the reference coordinate, an appropriate mathematical model was employed to establish the functional relationship between the centerline velocity of the roadway and the dimensionless horizontal coordinate. The fitting results showed good agreement, and this model can be used to back-calculate and expand the potential installation locations for a mine anemometer.https://www.mdpi.com/2311-5521/10/4/77numerical simulationmine tunnelnon-dimensionalizationcharacteristic distribution
spellingShingle Zongcheng Jia
Qiang Zhao
Yan Zhao
Baoyu Cui
Tao Song
Dimensionless Analysis of Rough Roadway Airflow Distribution Based on Numerical Simulations
Fluids
numerical simulation
mine tunnel
non-dimensionalization
characteristic distribution
title Dimensionless Analysis of Rough Roadway Airflow Distribution Based on Numerical Simulations
title_full Dimensionless Analysis of Rough Roadway Airflow Distribution Based on Numerical Simulations
title_fullStr Dimensionless Analysis of Rough Roadway Airflow Distribution Based on Numerical Simulations
title_full_unstemmed Dimensionless Analysis of Rough Roadway Airflow Distribution Based on Numerical Simulations
title_short Dimensionless Analysis of Rough Roadway Airflow Distribution Based on Numerical Simulations
title_sort dimensionless analysis of rough roadway airflow distribution based on numerical simulations
topic numerical simulation
mine tunnel
non-dimensionalization
characteristic distribution
url https://www.mdpi.com/2311-5521/10/4/77
work_keys_str_mv AT zongchengjia dimensionlessanalysisofroughroadwayairflowdistributionbasedonnumericalsimulations
AT qiangzhao dimensionlessanalysisofroughroadwayairflowdistributionbasedonnumericalsimulations
AT yanzhao dimensionlessanalysisofroughroadwayairflowdistributionbasedonnumericalsimulations
AT baoyucui dimensionlessanalysisofroughroadwayairflowdistributionbasedonnumericalsimulations
AT taosong dimensionlessanalysisofroughroadwayairflowdistributionbasedonnumericalsimulations