Reports on corrosion failure of cable bolts,used in mining and civil industries,have been increasing in the past two decades.The previous studies found that pitting corrosion on the surface of a cable bolt can initiat...Reports on corrosion failure of cable bolts,used in mining and civil industries,have been increasing in the past two decades.The previous studies found that pitting corrosion on the surface of a cable bolt can initiate premature failure of the bolt.In this study,the role of Acidithiobacillus ferrooxidans(A.ferrooxidans)bacterium in the occurrence of pitting corrosion in cable bolts was studied.Stressed coupons,made from the wires of cable bolts,were immersed in testing bottles containing groundwater collected from an underground coal mine and a mixture of A.ferrooxidans and geomaterials.It was observed that A.ferrooxidans caused pitting corrosion on the surface of cable bolts in the near-neutral environment.The presence of geomaterials slightly affected the p H of the environment;however,it did not have any significant influence on the corrosion activity of A.ferrooxidans.This study suggests that the common bacterium A.ferrooxidans found in many underground environments can be a threat to cable bolts'integrity by creating initiation points for other catastrophic failures such as stress corrosion cracking.展开更多
Forecasting mineral commodity(MC) prices has been an important and difficult task traditionally addressed by econometric, stochastic-Gaussian and time series techniques. None of these techniques has proved suitable to...Forecasting mineral commodity(MC) prices has been an important and difficult task traditionally addressed by econometric, stochastic-Gaussian and time series techniques. None of these techniques has proved suitable to represent the dynamic behavior and time related nature of MC markets. Chaos theory(CT) and machine learning(ML) techniques are able to represent the temporal relationships of variables and their evolution has been used separately to better understand and represent MC markets. CT can determine a system's dynamics in the form of time delay and embedding dimension. However, this information has often been solely used to describe the system's behavior and not for forecasting.Compared to traditional techniques, ML has better performance for forecasting MC prices, due to its capacity for finding patterns governing the system's dynamics. However, the rational nature of economic problems increases concerns regarding the use of hidden patterns for forecasting. Therefore, it is uncertain if variables selected and hidden patterns found by ML can represent the economic rationality.Despite their refined features for representing system dynamics, the separate use of either CT or ML does not provide the expected realistic accuracy. By itself, neither CT nor ML are able to identify the main variables affecting systems, recognize the relation and influence of variables though time, and discover hidden patterns governing systems evolution simultaneously. This paper discusses the necessity to adapt and combine CT and ML to obtain a more realistic representation of MC market behavior to forecast long-term price trends.展开更多
Assessment of mining impact on groundwater is one of critical considerations for longwall extension and sustainability,however usually constrained by limited data availability,hydrogeological variation,and the complex...Assessment of mining impact on groundwater is one of critical considerations for longwall extension and sustainability,however usually constrained by limited data availability,hydrogeological variation,and the complex coupled hydro-mechanical behaviour.This paper aims to determine the factors and mechanism of groundwater depressurisation and identify knowledge gaps and methodological limitations for improving groundwater impact assessment.Analysis of dewatering cases in Australian,Chinese,and US coalfields demonstrates that piezometric drawdown can further lead to surface hydrology degradation,while the hydraulic responses vary with longwall parameters and geological conditions.Statistical interpretation of 422 height of fracturing datasets indicates that the groundwater impact positively correlates to panel geometry and depth of cover,and more pronounced in panel interaction and top coal caving cases.In situ stress,rock competency,clay mineral infillings,fault,valley topography,and surface-subsurface water interaction are geological and hydrogeological factors influencing groundwater hydraulics and long-term recovery.The dewatering mechanism involves permeability enhancement and extensive flow through fracture networks,where interconnected fractures provide steep hydraulic gradients and smooth flow pathways draining the overlying water to goaf of lower heads.Future research should improve fracture network identification and interconnectivity quantification,accompanied by description of fuid flow dynamics in the high fracture frequency and large fracture aperture context.The paper recommends a research framework to address the knowledge gaps with continuous data collection and field-scale numerical modelling as key technical support.The paper consolidates the understanding of longwall mining impacting mine hydrology and provides viewpoints that facilitate an improved assessment ofgroundwaterdepressurisation.展开更多
基金funding provided by the Australian Research Council(ARC)Linkage Projects(Nos.100200238 and 140100153)supported by Jennmar Australia Pty Ltd+5 种基金Glencore Australia Holdings Pty LtdIllawarra Coal Holdings Pty LtdSpringvale Coal Pty LtdAnglo Operations Pty LtdAnglo Coal AustraliaNarrabri Coal Operations Pty Ltd。
文摘Reports on corrosion failure of cable bolts,used in mining and civil industries,have been increasing in the past two decades.The previous studies found that pitting corrosion on the surface of a cable bolt can initiate premature failure of the bolt.In this study,the role of Acidithiobacillus ferrooxidans(A.ferrooxidans)bacterium in the occurrence of pitting corrosion in cable bolts was studied.Stressed coupons,made from the wires of cable bolts,were immersed in testing bottles containing groundwater collected from an underground coal mine and a mixture of A.ferrooxidans and geomaterials.It was observed that A.ferrooxidans caused pitting corrosion on the surface of cable bolts in the near-neutral environment.The presence of geomaterials slightly affected the p H of the environment;however,it did not have any significant influence on the corrosion activity of A.ferrooxidans.This study suggests that the common bacterium A.ferrooxidans found in many underground environments can be a threat to cable bolts'integrity by creating initiation points for other catastrophic failures such as stress corrosion cracking.
文摘Forecasting mineral commodity(MC) prices has been an important and difficult task traditionally addressed by econometric, stochastic-Gaussian and time series techniques. None of these techniques has proved suitable to represent the dynamic behavior and time related nature of MC markets. Chaos theory(CT) and machine learning(ML) techniques are able to represent the temporal relationships of variables and their evolution has been used separately to better understand and represent MC markets. CT can determine a system's dynamics in the form of time delay and embedding dimension. However, this information has often been solely used to describe the system's behavior and not for forecasting.Compared to traditional techniques, ML has better performance for forecasting MC prices, due to its capacity for finding patterns governing the system's dynamics. However, the rational nature of economic problems increases concerns regarding the use of hidden patterns for forecasting. Therefore, it is uncertain if variables selected and hidden patterns found by ML can represent the economic rationality.Despite their refined features for representing system dynamics, the separate use of either CT or ML does not provide the expected realistic accuracy. By itself, neither CT nor ML are able to identify the main variables affecting systems, recognize the relation and influence of variables though time, and discover hidden patterns governing systems evolution simultaneously. This paper discusses the necessity to adapt and combine CT and ML to obtain a more realistic representation of MC market behavior to forecast long-term price trends.
文摘Assessment of mining impact on groundwater is one of critical considerations for longwall extension and sustainability,however usually constrained by limited data availability,hydrogeological variation,and the complex coupled hydro-mechanical behaviour.This paper aims to determine the factors and mechanism of groundwater depressurisation and identify knowledge gaps and methodological limitations for improving groundwater impact assessment.Analysis of dewatering cases in Australian,Chinese,and US coalfields demonstrates that piezometric drawdown can further lead to surface hydrology degradation,while the hydraulic responses vary with longwall parameters and geological conditions.Statistical interpretation of 422 height of fracturing datasets indicates that the groundwater impact positively correlates to panel geometry and depth of cover,and more pronounced in panel interaction and top coal caving cases.In situ stress,rock competency,clay mineral infillings,fault,valley topography,and surface-subsurface water interaction are geological and hydrogeological factors influencing groundwater hydraulics and long-term recovery.The dewatering mechanism involves permeability enhancement and extensive flow through fracture networks,where interconnected fractures provide steep hydraulic gradients and smooth flow pathways draining the overlying water to goaf of lower heads.Future research should improve fracture network identification and interconnectivity quantification,accompanied by description of fuid flow dynamics in the high fracture frequency and large fracture aperture context.The paper recommends a research framework to address the knowledge gaps with continuous data collection and field-scale numerical modelling as key technical support.The paper consolidates the understanding of longwall mining impacting mine hydrology and provides viewpoints that facilitate an improved assessment ofgroundwaterdepressurisation.
