Genetic programming for prediction of heat stress hazard in underground coal mine environment

Siddhartha Roy, Devi Prasad Mishra (), Ram Madhab Bhattacharjee and Hemant Agrawal
Additional contact information
Siddhartha Roy: Indian Institute of Technology (Indian School of Mines)
Devi Prasad Mishra: Indian Institute of Technology (Indian School of Mines)
Ram Madhab Bhattacharjee: Indian Institute of Technology (Indian School of Mines)
Hemant Agrawal: Central Mine Planning and Design Institute Ltd.

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2022, vol. 114, issue 3, No 6, 2527-2543

Abstract: Abstract Working against nature and an uncertain environment makes underground mining a hazardous profession. Every year hundreds of miners lose their valuable lives due to mine hazards. Increasing demand for coal necessitates the extraction of coal at a higher rate. As a result, easily minable shallow coal deposits are depleting speedily, and in near future, deep-seated deposits will be left for mining by underground methods. With rising depth and deployment of high-capacity machines, increasing heat stress becomes a major hazard in the underground mine environment posing threat to the miners’ health, productivity and safety. Ignoring the effect of heat stress may lead to dangerous circumstances, even result in death. To avoid such unwanted event, it has become imperative to predict the heat stress to reduce its adverse impact in underground coal mines. Therefore, in this study a detailed field survey is conducted to collect the environmental data of three underground coal mines. Genetic programming (GP) is done to develop a relation between the environmental parameters and heat stress, by taking the mine survey data as input. A good correlation coefficient (R = 0.9816) is obtained between the GP predicted heat stress and actually measured heat stress, which indicates that GP can be effectively used to predict the heat stress in underground mines. A sensitivity analysis (SA) is done to determine the effect of input parameters on heat stress. The SA results revealed that all six input parameters have a considerable effect on the heat stress; however, the dry-bulb temperature has the highest effect (0.98) on heat stress.

Keywords: Heat stress hazard; Underground mine environment; Miners’ safety and health; Heat-related illness; Genetic programming; Sensitivity analysis (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://link.springer.com/10.1007/s11069-022-05478-6 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:nathaz:v:114:y:2022:i:3:d:10.1007_s11069-022-05478-6

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/11069

DOI: 10.1007/s11069-022-05478-6

Access Statistics for this article

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards is currently edited by Thomas Glade, Tad S. Murty and Vladimír Schenk

More articles in Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards from Springer, International Society for the Prevention and Mitigation of Natural Hazards
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().