Numerical simulation of air ventilation in super-large underground developments

Li, Ming; Wu, Chao

doi:10.1016/j.tust.2015.11.009

Cited by 55 publications

(13 citation statements)

References 17 publications

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“…Coal resources account for 70% and 60% of the primary energy production and consumption structure, respectively, and they have always been the main energy source of China. In recent years, the mining scale and intensity of coal mines have gradually increased with the prosperity of coal production each year, and many large and super‐large section chambers and chamber groups have emerged . The cluster distribution of super‐large section chambers makes the interaction between the chambers fierce, and it is very easy to cause dynamic accidents such as roof fall and rib spalling.…”

Section: Introductionmentioning

confidence: 99%

Numerical investigation of failure evolution for the surrounding rock of a super‐large section chamber group in a deep coal mine

Tan

Fan

Liu

et al. 2019

Energy Science & Engineering

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The stability control of surrounding rock for a large or super‐large section chamber group is a difficult technical problem in deep mining conditions, and this stability control has become one of the most important factors restricting the safety of a large‐scale coal mine. Based on the in‐site geological conditions of a super‐large section chamber group that functions for a coal gangues separation system in the Longgu Coal Mine, we first researched the stress, deformation, and failure characteristics of the in‐site chamber group surrounding rocks by using the FLAC3D software. Simulation results showed that the maximum vertical stress, deformation, and failure range of the surrounding rock for a super‐large section chamber group are larger than those of an ordinary section chamber. In addition, the roof subsidence and the plastic zone radius at the intersection are obviously larger than that of other parts, which increase by approximately 50.8% and 44.4%, respectively. Therefore, the chamber group intersection should be taken as the key area for surrounding rock control. Then, the influences of two key parameters of the chamber group, spacing and angle, were researched in detail to help in the design of the chamber group. Results show that when the chamber spacing is 80 m, the interaction begins to occur. When the angle is 70°, the stress of the surrounding rock and roof subsidence reach the minimum. Thus, the optimum chamber group parameters are determined to be a spacing of 80 m and an angle of 70°. Finally, from the perspective of chamber group stability, the optimal chamber group parameters can better meet the normal use for the super‐large section chamber group. This research provides a reference for the design of a super‐large section chamber group under the same or similar conditions and provides a strategy for controlling the surrounding rock.

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Section: Introductionmentioning

confidence: 99%

Numerical investigation of failure evolution for the surrounding rock of a super‐large section chamber group in a deep coal mine

Tan

Fan

Liu

et al. 2019

Energy Science & Engineering

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“…The dead zone is the area in which the ventilating flow is not capable of sweeping the blasting gases. For practical reasons, several authors and legislations have defined the dead zone as that where the air velocity is at most 0.5 m/s [19] or, less restrictively, at most 0.15 m/s [18,25]. This definition, for a long period, implies that any air clearance is still possible until the air velocity is zero.…”

Section: Dead Zone Delimitationmentioning

confidence: 99%

“…Toraño et al (2009) [17] modeled methane behavior, but did not consider blasting gases, in coal mines ancillary ventilation. Li, Aminossadati and Wu [18] studied ancillary ventilation in super large developments. Onder, Sarac and Cevik studied the ventilation of a cul-de-sac, but focused on fan-duct interaction rather than on the flow outside the duct.…”

Section: Introductionmentioning

confidence: 99%

A Discussion on the Effective Ventilation Distance in Dead-End Tunnels

et al. 2019

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Forcing ventilation is the most widely used system to remove noxious gases from a working face during tunnel construction. This system creates a region near the face (dead zone), in which ventilation takes place by natural diffusion, rather than being directly swept by the air current. Despite the extensive use of this system, there is still a lack of parametrical studies discerning the main parameters affecting its formation as well as a correlation indicating their interrelation. With this aim in mind, computational fluid dynamics (CFDs) models were used to define the dead zone based on the airflow field patterns. The formation of counter vortices, which although maintain the movement of air hinder its renewal, allowed us to discuss the old paradigm of defining the dead zone as a very low air velocity zone. Moreover, further simulations using a model of air mixed with NO 2 offered an idea of NO 2 concentrations over time and distance to the face, allowing us to derive at a more realistic equation for the effective distance. The results given here confirm the degree of conservativism of present-day regulations and may assist engineers to improve ventilation efficiency in tunnels by modifying the duct end-to-face distance.

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“…Cheng et al [53] modelled the impact of different ventilation parameters on goaf gas distribution with due consideration of balanced goaf gas control and fire prevention. Li et al [54] studied the ventilation flow characteristics in super-large subsurface tunnels and concluded that the minimum air velocity should be greater than 0.15 m/s to dilute the CO concentration below statutory level within 20 min. Xia et al [55] numerically investigated the ventilation and dust flow behaviour in open-type TBM tunnelling work area and optimised the ventilation configuration for optimal dust control.…”

Section: Review Of Cfd Modelling Of Underground Ventilation Systemsmentioning

confidence: 99%

Investigations of Ventilation Airflow Characteristics on a Longwall Face—A Computational Approach

Wang

Ren

et al. 2018

Energies

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Mine ventilation has always been critical for underground mining operations to ensure operational efficiency and compliance with safety and health statutory requirements. To obtain a thorough understanding of the ventilation flow characteristics on a longwall face, innovative three dimensional (3D) models, incorporating key features of the longwall equipment and a zone of immediate goaf area, were developed. Mesh independent studies were conducted to determine the desirable mesh required for a mesh-independent solution. Then the model results were validated using field ventilation survey data. At both intersections of maingate/tailgate (MG/TG) and face where the flow boundary changes sharply, the occurrence of undesirable flow separation which causes additional energy loss was identified, as well as its extent of influence. The recirculation of airflow resulting from separation in the TG will lead to accumulation of high concentrations of mine gas, thus regular inspection or continuous monitoring of gas concentration in that area is highly recommended, especially when high gas emission is expected from the working seam. In addition, we also investigated the influence of shearer position and cutting sequence on longwall ventilation. Overall, the longwall models developed in this study together with the flow characteristics obtained will provide fundamental basis for the investigation of longwall gas and dust issues in the future.

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Numerical simulation of air ventilation in super-large underground developments

Cited by 55 publications

References 17 publications

Numerical investigation of failure evolution for the surrounding rock of a super‐large section chamber group in a deep coal mine

Numerical investigation of failure evolution for the surrounding rock of a super‐large section chamber group in a deep coal mine

A Discussion on the Effective Ventilation Distance in Dead-End Tunnels

Investigations of Ventilation Airflow Characteristics on a Longwall Face—A Computational Approach

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