Last data update: May 13, 2024. (Total: 46773 publications since 2009)
Records 1-8 (of 8 Records) |
Query Trace: Bahrami D[original query] |
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Identifying the location and size of an underground mine fire with simulated ventilation data and random forest model
Xue Y , Bahrami D , Zhou L . Min Metall Explor 2023 Underground mine fires are a threat to the safety and health of mine workers. The timely determination of the location and size of an underground fire is of great importance in developing firefighting strategies and reducing the risk of any injuries. Machine learning was used in this paper to develop a predictive model for fire location and fire size in an underground mine. The ventilation data were obtained by simulating different mine fire scenarios with MFire. The ventilation data of all airways were used as features to predict the fire location. Based on the feature importance, five airways were selected to monitor, and the airflow data of the selected airways were used to predict the fire location and fire size. An accuracy score of 0.920 was obtained for the prediction of fire location. In addition, in-depth analyses were conducted to characterize the wrong predictions with the purpose of improving the performance of the random forest model. The results show that the occurrence of fire at closely connected airways at some locations can generate misleading ventilation data for each other and the model performance can be further improved to 0.962 by grouping them. Fire size is another factor affecting the model performance and the model accuracy increases with increasing fire size. The result from this study can help mine safety personnel make informed decisions during a mine fire emergency. © 2023, This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply. |
Hot surface ignition of liquid fuels under ventilation
Tang W , Bahrami D , Yuan L , Thomas R , Soles J . Min Metall Explor 2022 39 (3) 961-968 Mine equipment fires remain as one of the most concerning safety issues in the mining industry, and most equipment fires were caused by hot surface ignitions. Detailed experimental investigations were conducted at the NIOSH Pittsburgh Mining Research Division on hot surface ignition of liquid fuels under ventilation in a mining environment. Three types of metal surface materials (stainless steel, cast iron, carbon steel), three types of liquids (diesel fuel, hydraulic fluid, engine oil), four air ventilation speeds (0, 0.5, 1.5, 3 m/s) were used to study the hot surface ignition probability under these conditions. Visual observation and thermocouples attached on the metal surface were used to indicate the hot surface ignition from the measured temperatures. Results show that the type of metal has a noticeable effect on the hot surface ignition, while ventilation speed has a mixed influence on ignition. Different types of liquid fuels also show different ranges of ignition temperatures. Results from this work can be used to help understand equipment mine fires and develop mitigation strategies. |
A derivative method to calculate resistance sensitivity for mine ventilation networks
Zhou L , Bahrami D . Min Metall Explor 2022 39 (4) 1833-1839 A reliable and stable ventilation system is essential to the safe operation of underground mines. The stability of a mine ventilation system becomes extremely critical while responding to a fire incident since an unstable ventilation system will pose a risk of airflow reversal. The reversed airflow could bring the fire contaminants such as toxic gases and smoke unexpectedly to working areas. In the past few years, there has been a growing interest in the study of ventilation network stability using the concept of resistance sensitivity, which is described as an indicator of how the airflow in an airway is reacting to a resistance change of other airways. Several methods of calculating the resistance sensitivity in a mine ventilation network have been carried out by researchers and scholars around the world. However, the proposed methods heavily rely on a vast amount of mine ventilation simulations, which are very time consuming and computer-power intensive, especially for a large-scale mine ventilation network. In this paper, a derivative method calculating the resistance sensitivities with a single mine ventilation simulation has been developed and implemented into a mine fire simulation software, MFIRE. The results from the derivative method were verified against the results from a traditional method. The derivative method has been proven to be reliable and accurate. 2022, This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply. |
Experimental study of improving a mine ventilation network model using continuously monitored airflow
Zhou L , Thomas RA , Yuan L , Bahrami D . Min Metall Explor 2022 39 (3) 887-895 A calibrated and well-tuned ventilation network model plays a critical role in mine ventilation planning, optimization, and ventilation control. Moreover, it is critical to the mine fire simulation program as well since the fire simulation is built upon the mine ventilation model. The contaminants generated from a fire are transported by airflows throughout the mine ventilation system. The accuracy of the fire simulation results not only depends on the fire source model itself but also on the ventilation network model. With the increasing use of atmospheric monitoring systems in underground mines, airflow is continuously monitored using airflow sensors in the key areas of mines to ensure a steady and reliable ventilation. Experimental studies have been conducted at an experimental mine, the Safety Research Coal Mine (SRCM), to gain a better understanding on how to use the continuously monitored airflow data to improve the calibration of the mine ventilation network model. This paper introduces an improved method to calibrate a ventilation network using continuous airflow monitoring and addresses the practical problems encountered while calibrating and tuning the ventilation network of the SRCM using continuously monitored airflow data. In this study, the fluctuation of the air velocity sensor readings is analyzed, and the sensor location correction factors are applied to obtain a more accurate average air velocity for the ventilation network calibration. © 2022, This is a U.S. government work and not under copyright protection in the U.S.; foreign copyright protection may apply. |
Field verification of an improved mine fire location model
Bahrami D , Zhou L , Yuan L . Min Metall Explor 2020 38 (1) 559-566 Underground mine fires remain a concern for mine operators, posing a health and safety risk to mineworkers. In the last decade, the number of mine fires has decreased significantly; however, dealing with an unknown fire in underground mines can be a challenging task, which could lead to a hazardous condition for miners during an evacuation and rescue operation. A timely detection of a mine fire and monitoring its characteristics, namely size and location, are of great importance in reducing the risk of mine fire injuries. A new improved fire location algorithm has been developed and integrated into an Atmospheric Monitoring System (AMS) program by researchers from the National Institute for Occupational Safety and Health (NIOSH). This paper describes the new fire location model and presents the results of verification fire tests conducted at the Safety Research Coal Mine (SRCM) facility of the Pittsburgh Mining Research Division (PMRD) using the collected AMS data. NIOSH is endeavoring to develop workplace solutions to improve detection of and reduce the risk of hazardous conditions in mines. The results demonstrate successful application of the improved fire location model and provide a useful tool for solving the problem of unknown fire location and reducing the risk of hazardous conditions. |
An improved method to calculate the heat release rate of a mine fire in underground mines
Zhou L , Yuan L , Thomas R , Bahrami D , Rowland J . Min Metall Explor 2020 37 (6) 1941-1949 Continuous monitoring of carbon monoxide and other fire-related parameters by means of an atmospheric monitoring system (AMS) has been used by the mining industry for early fire detection in underground mines. The National Institute for Occupational Safety and Health (NIOSH) initiated a project to integrate real-time AMS sensor data with NIOSH’s mine fire simulation program, MFIRE 3.0, to simulate and predict the spread of smoke that would provide assistance to mine fire emergency response personnel. Determining the heat release rate of a fire using the monitored sensor data was a critical component of the successful completion of this project. NIOSH researchers developed a direct method to calculate the heat release rate when a fire is within close range of sensors. However, this method is only applicable to the case where a fire occurs in AMS-monitored airways. This paper presents an improved method for determining the fire heat release rate for complicated scenarios where a fire is distant from sensors and airflow splits and merges are present. The method was validated using a full-scale diesel fuel fire test conducted in the Safety Research Coal Mine at the Pittsburgh Mining Research Division and can help mine operators and safety personnel make informed decisions during a fire emergency. |
Evaluation of post-blast re-entry times based on gas monitoring of return air
Bahrami D , Yuan L , Rowland JH , Zhou L , Thomas R . Min Metall Explor 2019 36 (3) 513-521 Blasting is the main method of production in many non-coal underground mining operations and produces multiple toxic gases as a result. The Mine Safety and Health Administration (MSHA) requires mine operators to measure the level of toxic gases in mines as frequently as necessary to ensure they are below regulatory safety limits. The current practice uses portable gas monitors to check the concentrations of toxic gases after a fixed post-blast time. This paper studies the application of a gas monitoring system in the return entry of a limestone mine to determine a safe re-entry time. The National Institute for Occupational Safety and Health (NIOSH) conducted such a monitoring program in a limestone mine from September 2016 through May 2018. NIOSH/PMRD (Pittsburgh Mining Research Division) is endeavoring to develop workplace solutions to improve detection of and reduce the risk of hazardous conditions. This study showed that the use of gas monitoring in the return air can be a useful tool at the mine operator's disposal to detect and reduce the risk of hazardous conditions and also to reliably estimate the re-entry time. |
Numerical and experimental investigation of carbon monoxide spread in underground mine fires
Zhou L , Yuan L , Bahrami D , Thomas RA , Rowland JH . J Fire Sci 2018 36 (5) 406-418 The primary danger with underground mine fires is carbon monoxide poisoning. A good knowledge of smoke and carbon monoxide movement in an underground mine during a fire is of importance for the design of ventilation systems, emergency response, and miners escape and rescue. Mine fire simulation software packages have been widely used to predict carbon monoxide concentration and its spread in a mine for effective mine fire emergency planning. However, they are not highly recommended to be used to forecast the actual carbon monoxide concentration due to lack of validation studies. In this article, MFIRE, a mine fire simulation software based on ventilation networks, was evaluated for its carbon monoxide spread prediction capabilities using experimental results from large-scale diesel fuel and conveyor belt fire tests conducted in the Safety Research Coal Mine at The National Institute for Occupational Safety and Health. The comparison between the simulation and test results of carbon monoxide concentration shows good agreement and indicates that MFIRE is able to predict the carbon monoxide spread in underground mine fires with confidence. The Author(s) 2018. |
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