Study on the influence of radiation heat transfer on microclimatic parameters in the blind heading of a deep potash mine

Olkhovsky, Dmitry; Zaitsev, Artem; Bublik, Sergey

doi:10.1016/j.ijthermalsci.2024.108904

Cited by 1 publication

(1 citation statement)

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“…It is in this context that AI technologies are being integrated into mine ventilation systems today. Physical processes within mine atmospheres are well-understood by engineers and scientists and are typically modeled using deterministic approaches, such as solving systems of Kirchhoff equations to determine air distribution and solving differential equations for convective-diffusion transfer of heat and harmful impurities through mine workings (Olkhovsky et al, 2024 ).…”

Section: Discussionmentioning

confidence: 99%

Application of artificial intelligence in mine ventilation: a brief review

Semin,

Kormshchikov

2024

Front. Artif. Intell.

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In recent years, there has been a notable integration of artificial intelligence (AI) technologies into mine ventilation systems. A mine ventilation network presents a complex system with numerous interconnected processes, some of which pose challenges for deterministic simulation methods. The utilization of machine learning techniques and evolutionary algorithms offers a promising avenue to address these complexities, resulting in enhanced monitoring and control of air parameter distribution within the ventilation network. These methods facilitate the timely identification of resistance faults and enable prompt calculation of ventilation parameters during emergency scenarios, such as underground explosions and fires. Furthermore, evolutionary algorithms play a crucial role in the advancement of methods for visual analysis of ventilation systems. However, it is essential to acknowledge that the current utilization of AI technologies in mine ventilation is limited and does not encompass the full spectrum of challenging-to-formalize problems. Promising areas for AI application include analyzing changes in air distribution caused by unaccounted thermal draft and gas pressure, as well as developing novel approaches for calculating shock losses. Moreover, the application of AI technologies in optimizing large-scale mine ventilation networks remains an unresolved issue. Addressing these challenges holds significant potential for enhancing safety and efficiency in mine ventilation systems.

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Section: Discussionmentioning

confidence: 99%