Development of a Respirable Dust Mitigation System for a High Longwall Face at Sihe Colliery in China â a Case Study

Dust is a major hazard in underground coal mines that threatens the work health and safety of coal miners. The dust issue becomes increasingly significant with the development of highly mechanized coal mining. This issue is particularly serious at the high longwall faces of the Sihe colliery in China as the concentration of dust, in particular respirable dust, at these faces far exceeds the regulatory dust limits. Field testing and computational fluid dynamics (CFD) simulations were conducted to understand the sources of dust generation and its dynamic movement in the #5301 longwall face of high-cutting height at the colliery. The investigation results showed that shearer generated dust was minimal during the coal cutting operation; that face spalling and chock movement were the main dust generating sources, causing significant contamination to the walkway; and that the majority of dust particles from the face (regardless of source) eventually disperse into the main gate, where the dust concentration was greater than 500 mg/m3. These findings were used to develop an effective coal dust mitigation system involving the installation of dust scrubbers, curtains, and venture and crescent sprays. The results of CFD modeling indicate that the dust concentration could be significantly reduced by adopting the new dust mitigation system

Development of a Respirable Dust Mitigation System for a High Longwall Face at Sihe Colliery in China – a Case Study

Dust is a major hazard in underground coal mines that threatens the work health and safety of coal miners. The dust issue becomes increasingly significant with the development of highly mechanized coal mining. This issue is particularly serious at the high longwall faces of the Sihe colliery in China as the concentration of dust, in particular respirable dust, at these faces far exceeds the regulatory dust limits. Field testing and computational fluid dynamics (CFD) simulations were conducted to understand the sources of dust generation and its dynamic movement in the #5301 longwall face of high-cutting height at the colliery. The investigation results showed that shearer generated dust was minimal during the coal cutting operation; that face spalling and chock movement were the main dust generating sources, causing significant contamination to the walkway; and that the majority of dust particles from the face (regardless of source) eventually disperse into the main gate, where the dust concentration was greater than 500 mg/m3. These findings were used to develop an effective coal dust mitigation system involving the installation of dust scrubbers, curtains, and venture and crescent sprays. The results of CFD modeling indicate that the dust concentration could be significantly reduced by adopting the new dust mitigation system

Modelling the impact of social network on energy savings

It is noted that human behaviour changes can have a significant impact on energy consumption, however, qualitative study on such an impact is still very limited, and it is necessary to develop the corresponding mathematical models to describe how much energy savings can be achieved through human engagement. In this paper a mathematical model of human behavioural dynamic interactions on a social network is derived to calculate energy savings. This model consists of a weighted directed network with time evolving information on each node. Energy savings from the whole network is expressed as mathematical expectation from probability theory. This expected energy savings model includes both direct and indirect energy savings of individuals in the network. The savings model is obtained by network weights and modified by the decay of information. Expected energy savings are calculated for cases where individuals in the social network are treated as a single information source or multiple sources. This model is tested on a social network consisting of 40 people. The results show that the strength of relations between individuals is more important to information diffusion than the number of connections individuals have. The expected energy savings of optimally chosen node can be 25.32% more than randomly chosen nodes at the end of the second month for the case of single information source in the network, and 16.96% more than random nodes for the case of multiple information sources. This illustrates that the model presented in this paper can be used to determine which individuals will have the most influence on the social network, which in turn provides a useful guide to identify targeted customers in energy efficiency technology rollout programmes