Analysis of the damage mechanism of strainbursts by a global-local modeling approach

Wang, Jun; Apel, Derek B.; Dyczko, Artur; Walentek, Andrzej; Prusek, S.; Xu, Huawei; Wei, Chenyu

doi:10.1016/j.jrmge.2022.01.009

Cited by 23 publications

(11 citation statements)

References 56 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The connections between neurons have associated weights, which are adjusted during the training process to optimize the network's performance. This learning process, often referred to as backpropagation, involves iteratively comparing the network's predicted output with the desired output and adjusting the weights accordingly to minimize the prediction errors (Wang et al, 2022). Neural network models are based in forming similarity theorems in artificial neurons and their interconnections, which enable the networks to learn and make predictions based on the provided input data (Vladyko et al, 2022a).…”

Section: Indicators For Estimation Research Parametersmentioning

confidence: 99%

Real-Time Forecasting of Key Coking Coal Quality Parameters Using Neural Networks and Artificial Intelligence

Dyczko

2023

MGPB

View full text Add to dashboard Cite

High quality coke is a key raw material for the metallurgical industry. The characteristics of the coal have a significant influence on the parameters of the coke produced and, consequently, on the valuation of coal deposits and the economic assessment of mining projects. Predicting the quality of coking coal allows for the optimisation of production processes, including the planning and management of operations and the early detection of quality problems. In this study, using the principles of a smart mine, it is proposed to determine the quality of coal based on the combination of mining and geological conditions of mineral deposits and its quality indicators. Possible interrelationships between the quality of the coal in the deposit and the characteristics of the final product have been identified. A neural network is used to determine the priority of individual indicators that have a significant impact on the quality of coking coal. An important part of the research is its practical implementation in the conditions of the Jastrzębska Spółka Węglowa SA. Qualitative and quantitative parameters of coking coals were obtained for each mine of the region by the method of sampling and statistical processing of data such as: degree of metamorphism, thickness, deviation of volatile substances, presence of phosphorus, ash content, etc. For their evaluation, the Group Method of Data Handling was used to compare the factors of quality indicators depending on the priority of influence on the final characteristics of the coking coal. Based on the results obtained, it is shown that not all coal quality indicators have a significant impact on the quality of the final product. The study shows that it is possible to predict the main indicators (CRI – Coke Reactivity Index, CSR – Coke Strength after Reaction) of coke quality using neural networks based on a larger number of coal quality parameters and to eliminate parameters that have virtually no influence on the value of the final product. This method can also be used to improve the results of economic valuation of a deposit and to better plan exploration and mining operations.

show abstract

Section: Indicators For Estimation Research Parametersmentioning

confidence: 99%

Real-Time Forecasting of Key Coking Coal Quality Parameters Using Neural Networks and Artificial Intelligence

Dyczko

2023

MGPB

View full text Add to dashboard Cite

show abstract

“…The finite element (FE) numerical analysis model is capable to conduct general study and helping the engineer to understand better the “real world” of the underground space [ 40 , 41 , 42 , 43 , 44 , 45 ]. Model calibration is a vital step in checking the reliability of the developed numerical model by comparing the monitored and recorded in situ data with the computed data from the developed numerical model.…”

Section: Calibration and Verification Of The Finite Element (Fe) Modelmentioning

confidence: 99%

Investigation and Stability Assessment of Three Sill Pillar Recovery Schemes in a Hard Rock Mine

Apel

Wang

et al. 2022

Energies

Self Cite

View full text Add to dashboard Cite

In Canada, many mines have adopted the sublevel stoping method, such a blasthole stoping (BHS), to extract steeply deposited minerals. Sill pillars are usually kept in place in this mining method to support the weight of the overburden in underground mining. To prolong the mine’s life, sill pillars will be recovered, and sill pillar recovery could cause failures, fatality, and equipment loss in the stopes. In this paper, three sill pillar recovery schemes—SBS, SS1, and SS2—were proposed and conducted to assess the feasibility of recovering two sill pillars in a hard rock mine by developing a full-sized three-dimensional (3D) analysis model employing the finite element method (FEM). The numerical model was calibrated by comparing the model computed ground settlement with the in situ monitored ground settlement data. The rockburst tendency of the stope accesses caused by the sill pillar recovery was assessed by employing the tangential stress (Ts) criterion and burst potential index (BPI) criterion. All three proposed sill pillar recovery schemes were feasible and safe to recover the sill pillars in this hard rock mine, and the scheme SBS was the optimum one among the three schemes.

show abstract

“…The method of internal dumping using controlled rock deformations with a temporary crest of bench in a depleted deep open pit, flooded with groundwater, with steep slope inclination angles has been studied in detail [42][43][44]. The analysis in these studies showed that mass dumped by dragline tends to slide.…”

Section: Introductionmentioning

confidence: 99%

Determining the Safe Distance for Mining Equipment Operation When Forming an Internal Dump in a Deep Open Pit

et al. 2023

View full text Add to dashboard Cite

In the surface mining of mineral deposits, land resources suitable for agricultural purposes are inappropriately spent in large volumes. When mining deep open pits, overburden rocks are mainly transported to the surface. The optimal solution for reducing the area of disturbed lands is the placement of overburden rocks in internal dumps in the open pit. This is especially suitable when mining a mineral deposit with several open pits where at least one of them is depleted. Therefore, it is important to assess the feasibility of building an internal dump, based on the stability parameters of its slopes and the safe distance for placing mining equipment within its boundaries, which was the focus of this research. Numerical modeling with Slide 5.0 software was used to determine the stability of the dump slope inside the open pit and the safe distance from the upper slope edge for placing mining equipment. This reflected the geomechanical situation occurring within the boundaries of the dump formed in the open-pit field with a high degree of reliability. It was determined that the maximum standard safety factor values of the open-pit slopes are within the limits when the overburden rocks border on the hard bedrock (Ks.s.f ≥ 1.2). Under the condition where the dump slope bordered on sedimentations represented by clays, loams, and sands with a strength of 2–3 on the Mohs scale, the safety factor decreased by 22%. It was determined that the minimum safe distance from the outer contour of the dragline base to the upper edge of a single-tier dump was 15.5 m with a safety factor of 1.21. The maximum safe distance values in the range of 73.5–93 m were concentrated within the boundaries of sections 5–9, with a safety factor from 1.18 to 1.28. When the dragline was located within the boundaries of section 7, the dump construction works should be conducted only if the dump exist for up to 3 years. Based on the identified parameters, on the example of using the ESH-11/70 walking dragline, a technological scheme of its operation was developed with the allocation of safe boundaries for its placement when forming an internal dump. The results obtained are useful for the development of projects for the reclamation of depleted open pits.

show abstract

Analysis of the damage mechanism of strainbursts by a global-local modeling approach

Cited by 23 publications

References 56 publications

Real-Time Forecasting of Key Coking Coal Quality Parameters Using Neural Networks and Artificial Intelligence

Real-Time Forecasting of Key Coking Coal Quality Parameters Using Neural Networks and Artificial Intelligence

Investigation and Stability Assessment of Three Sill Pillar Recovery Schemes in a Hard Rock Mine

Determining the Safe Distance for Mining Equipment Operation When Forming an Internal Dump in a Deep Open Pit

Contact Info

Product

Resources

About