| Summary: | 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.
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