As a new collaborative mining technology, the integration of mining-separating-backfilling (IMSB) enables the coal industry to realize safe, efficient, and green mining of coal resources at the expense of making the underground coal mine production more complex. In coal mining, the primary problem is to eliminate the production logistics system bottleneck to increase coal output. The key to synergetic mining is to realize that the mining capacity of the fully mechanized face should match the underground raw coal separating and gangue backfilling capacities. Considering a coal mine with IMSB in Henan Province, AnyLogic simulation software was used to simulate and optimize the production logistics system based on a generalized stochastic Petri net (GSPN). The main simulation results show that: (1) the raw coal separating capacity of this deep mine matches its mining capacity, and the gangue backfilling capacity can almost meet the demand for backfilling after raw coal mining; (2) belt conveyors 1 and 6 are the transportation bottlenecks of increasing production in the mine, and the lifting capacity of the main shaft is insufficient; (3) after optimization, the clean coal output of this coal mine increased by 3087 t monthly. This research promotes synergetic mining in the coal industry and can serve as a reference for the optimization of similar coal mine production logistics systems.
Clarifying the influencing factors of energy consumption in underground production processes of coal mine is the premise and foundation for the coal mining industry to control the energy consumption and intensity to achieve the goal of carbon peak and carbon neutrality. This paper aims to investigate and compare the differences in energy consumption and carbon emissions between a mining-separating-backfilling integrated coal mine (MSBICM) and a traditional coal mine and explore the effects of the main production links underground on carbon emission intensity in coal mines. Hence, taking an MSBICM in Henan province as an example, this study constructed an energy consumption and carbon emission model of the mine using system dynamics (SD) method. Based on this model, the energy consumption of the main production logistics system and auxiliary production system in MSBICM was simulated and analyzed. In addition, this study made a comparative analysis of the energy consumption of the different production links in the two types of coal mines. The results showed that: (1) the comprehensive mechanized coal mining with solid filling system and ventilation system were the subsystems with the highest and lowest energy consumption in MSBICM respectively. (2) The influence rates of raw coal mining, gangue filling, coal-gangue separating, and material transportation on carbon emission intensity in coal mine were 1.09%, 1.34%, 1.09%, and 5.13%, respectively. (3) Under the same production and filling targets, energy consumption of underground transportation systems in MSBICM was found to be 336.66 tons of standard coal less than that in traditional coal mine. This study has helped clarify the complex relationships among the factors that influence energy consumption in coal mines and provided a reference for implementing dual control of energy consumption to promote lowcarbon mining of coal resources.
How to improve the sustainability of resource-exhausted cities has become a difficult problem for China to implement the sustainable development strategy, and the construction of resilient cities has become the best way to solve this problem. This paper constructed an evaluation indicator system of the sustainable development for resource-exhausted cities from the perspective of resilient cities. The entropy weight-TOPSIS-grey relational degree model was used to quantitatively analyze the sustainable development capacity of 23 resource-exhausted cities in China from 2010 to 2020. And the coupling coordination degree model was further used to analyze the relationship between urban resilience and the dimensions of economy, environment, society and resource respectively. The weak links affecting their sustainable development was explored through obstacle degree model. The research results are helpful to fully understand the current situation and obstacle factors of the sustainable development of resource-exhausted cities in China, and promote the sustainable development of cities through the construction of resilient cities.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.