Temperature prediction model in the main ventilation system of an underground mine
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...
| Autores: | , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2020 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/330536 |
| Acceso en línea: | https://hdl.handle.net/2117/330536 https://dx.doi.org/10.3390/app10207238 |
| Access Level: | acceso abierto |
| Palabra clave: | Mine ventilation Potash mines and mining Mathematical models Work environment Underground mining Predictive model Temperature prediction Workplace environmental conditions Mines -- Ventilació Mines de potassa Models matemàtics Entorn de treball Àrees temàtiques de la UPC::Enginyeria civil::Enginyeria de mines |
| Sumario: | 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. |
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