Calibration of mine ventilation network models using the non-linear optimization algorithm
Effective ventilation planning is vital to underground mining. To ensure stable operation of the ventilation system and to avoid airflow disorder, mine ventilation network (MVN) models have been widely used in simulating and optimizing the mine ventilation system. However, one of the challenges f...
| Main Authors: | , , , , |
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| Format: | Journal Article |
| Published: |
2017
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| Online Access: | http://hdl.handle.net/20.500.11937/61465 |
| _version_ | 1848760687972581376 |
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| author | Xu, Guang Huang, J. Nie, B. Chalmers, D. Yang, Z. |
| author_facet | Xu, Guang Huang, J. Nie, B. Chalmers, D. Yang, Z. |
| author_sort | Xu, Guang |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Effective ventilation planning is vital to underground mining. To ensure stable operation
of the ventilation system and to avoid airflow disorder, mine ventilation network (MVN) models
have been widely used in simulating and optimizing the mine ventilation system. However, one
of the challenges for MVN model simulation is that the simulated airflow distribution results do
not match the measured data. To solve this problem, a simple and effective calibration method is
proposed based on the non-linear optimization algorithm. The calibrated model not only makes
simulated airflow distribution results in accordance with the on-site measured data, but also controls
the errors of other parameters within a minimum range. The proposed method was then applied to
calibrate an MVN model in a real case, which is built based on ventilation survey results and Ventsim
software. Finally, airflow simulation experiments are carried out respectively using data before
and after calibration, whose results were compared and analyzed. This showed that the simulated
airflows in the calibrated model agreed much better to the ventilation survey data, which verifies the
effectiveness of calibrating method. |
| first_indexed | 2025-11-14T10:19:45Z |
| format | Journal Article |
| id | curtin-20.500.11937-61465 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T10:19:45Z |
| publishDate | 2017 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-614652018-07-03T01:58:20Z Calibration of mine ventilation network models using the non-linear optimization algorithm Xu, Guang Huang, J. Nie, B. Chalmers, D. Yang, Z. Effective ventilation planning is vital to underground mining. To ensure stable operation of the ventilation system and to avoid airflow disorder, mine ventilation network (MVN) models have been widely used in simulating and optimizing the mine ventilation system. However, one of the challenges for MVN model simulation is that the simulated airflow distribution results do not match the measured data. To solve this problem, a simple and effective calibration method is proposed based on the non-linear optimization algorithm. The calibrated model not only makes simulated airflow distribution results in accordance with the on-site measured data, but also controls the errors of other parameters within a minimum range. The proposed method was then applied to calibrate an MVN model in a real case, which is built based on ventilation survey results and Ventsim software. Finally, airflow simulation experiments are carried out respectively using data before and after calibration, whose results were compared and analyzed. This showed that the simulated airflows in the calibrated model agreed much better to the ventilation survey data, which verifies the effectiveness of calibrating method. 2017 Journal Article http://hdl.handle.net/20.500.11937/61465 10.3390/en11010031 http://creativecommons.org/licenses/by/4.0/ fulltext |
| spellingShingle | Xu, Guang Huang, J. Nie, B. Chalmers, D. Yang, Z. Calibration of mine ventilation network models using the non-linear optimization algorithm |
| title | Calibration of mine ventilation network models using the non-linear optimization algorithm |
| title_full | Calibration of mine ventilation network models using the non-linear optimization algorithm |
| title_fullStr | Calibration of mine ventilation network models using the non-linear optimization algorithm |
| title_full_unstemmed | Calibration of mine ventilation network models using the non-linear optimization algorithm |
| title_short | Calibration of mine ventilation network models using the non-linear optimization algorithm |
| title_sort | calibration of mine ventilation network models using the non-linear optimization algorithm |
| url | http://hdl.handle.net/20.500.11937/61465 |