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...

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Main Authors: Marc Bascompta, Josep M. Rossell, Lluís Sanmiquel, Hernán Anticoi
Format: Article
Language:English
Published: MDPI AG 2020-10-01
Series:Applied Sciences
Subjects:
Online Access:https://www.mdpi.com/2076-3417/10/20/7238
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spelling doaj-73c3bed0c61c4fff8f8ced1ea30a04282020-11-25T03:51:08ZengMDPI AGApplied Sciences2076-34172020-10-01107238723810.3390/app10207238Temperature Prediction Model in the Main Ventilation System of an Underground MineMarc Bascompta0Josep M. Rossell1Lluís Sanmiquel2Hernán Anticoi3Department of Mining, Industrial and ICT Engineering, Polytechnic University of Catalonia (UPC), 08242 Barcelona, SpainDepartment of Mathematics, Polytechnic University of Catalonia (UPC), 08242 Barcelona, SpainDepartment of Mining, Industrial and ICT Engineering, Polytechnic University of Catalonia (UPC), 08242 Barcelona, SpainDepartment of Mining, Industrial and ICT Engineering, Polytechnic University of Catalonia (UPC), 08242 Barcelona, SpainA 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 <i>R</i><sup>2</sup> = 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.https://www.mdpi.com/2076-3417/10/20/7238underground miningmine ventilationpredictive modeltemperature predictionworkplace environmental conditions
collection DOAJ
language English
format Article
sources DOAJ
author Marc Bascompta
Josep M. Rossell
Lluís Sanmiquel
Hernán Anticoi
spellingShingle Marc Bascompta
Josep M. Rossell
Lluís Sanmiquel
Hernán Anticoi
Temperature Prediction Model in the Main Ventilation System of an Underground Mine
Applied Sciences
underground mining
mine ventilation
predictive model
temperature prediction
workplace environmental conditions
author_facet Marc Bascompta
Josep M. Rossell
Lluís Sanmiquel
Hernán Anticoi
author_sort Marc Bascompta
title Temperature Prediction Model in the Main Ventilation System of an Underground Mine
title_short Temperature Prediction Model in the Main Ventilation System of an Underground Mine
title_full Temperature Prediction Model in the Main Ventilation System of an Underground Mine
title_fullStr Temperature Prediction Model in the Main Ventilation System of an Underground Mine
title_full_unstemmed Temperature Prediction Model in the Main Ventilation System of an Underground Mine
title_sort temperature prediction model in the main ventilation system of an underground mine
publisher MDPI AG
series Applied Sciences
issn 2076-3417
publishDate 2020-10-01
description 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 <i>R</i><sup>2</sup> = 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.
topic underground mining
mine ventilation
predictive model
temperature prediction
workplace environmental conditions
url https://www.mdpi.com/2076-3417/10/20/7238
work_keys_str_mv AT marcbascompta temperaturepredictionmodelinthemainventilationsystemofanundergroundmine
AT josepmrossell temperaturepredictionmodelinthemainventilationsystemofanundergroundmine
AT lluissanmiquel temperaturepredictionmodelinthemainventilationsystemofanundergroundmine
AT hernananticoi temperaturepredictionmodelinthemainventilationsystemofanundergroundmine
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