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A model  to  forecast  the  underground  temperature  in  a mine  ventilation  circuit was developed on the basis of a case study and actual data describing temperature, airflow, and drift length  collected  over  several  years.  A  mathematical  model  featuring  seven  variables  with interactions provided reliable predicted temperatures, achieving a correlation of R2 = 0.933 with an estimation error of ±2 °C. Its soundness was proven using both the node‐to‐node analysis and the multi‐node approach. The multi‐node approach was shown to be an  interesting option to model underground mining  environments. This model  can  be  very  useful  to  predict  the  temperature evolution along the main ventilation system, determine the best workplace conditions in terms of temperature,  and  analyze  different  planning  scenarios  of  the  mine.  Moreover,  some recommendations are presented for obtaining reliable data when using temperature sensors and the model in a U‐shaped ventilation system.

Temperature Prediction Model in the Main Ventilation System of an Underground Mine