Underground Ventilation Research Articles

The Smallest “Miner” of the Animal Kingdom and Its Importance for Raw Materials Exploitation

The mining industry is the leading supplier of raw materials in modern society. This sector of human activity has experienced a severe crisis due to the energy transition and has been revived in recent years due to the need for critical metals that are essential in the post-coal era. In underground and open pit mining, processes such as extraction, transportation, safety, underground ventilation, waste management, and rehabilitation are of major importance, and their “design” is critical to the economic survival of the mine. All the above processes required to operate a mine are strongly reminiscent of an example of nature’s workman: the ant. The sympatric insect uses the same processes as the ones aforementioned during the creation of its nest. The ants dig to “extract material from the ground”, and they transport this material from the nest‘s site to the waste deposition location. The ants ensure the safety of the underground opening and the proper ventilation needed for them to live there for a long time. This article attempts to identify the relations between all the above processes and sub-processes, and how human mining and ant colony development correlate with each other. Furthermore, we examine how an ant colony has aided in the development of mining technology, and what more humans can learn and adopt from a “miner” that is 66 million years old, in order to improve their processes.

Incorporating temporal multi-head self-attention convolutional networks and LightGBM for indoor air quality prediction

Friction between subway wheels and tracks and inadequate combustion of fuel are causes of respirable particulate matter. Restricted underground ventilation and high population density make it difficult for particulate matter to dissipate, posing a threat to human health. An effective data-driven model for indoor pollutant prediction can enhance preparedness for high pollution situations. This study introduces a feature extraction method that combines kernel principal component analysis with max-relevance and min-redundancy algorithm. The temporal convolutional network, enhanced with a multi-head self-attention mechanism, adeptly captures time series features and effectively manages attention weight allocation. Additionally, the incorporation of the light gradient boosting machine method enhances overall efficiency. The proposed framework for PM2.5 concentration prediction was employed to a high-traffic subway station in Seoul. In the test set, the model demonstrated strong performance with evaluation metrics including an R2 value of 0.92, RMSE of 6.02 μg/m3, MAE of 4.36, and MAPE of 20.58 μg/m3. Compared to the conventional LSTM, the proposed method reduces the RMSE by 20.5% and the MAPE by 49.05%. Notably, the model we propose demonstrates superior capabilities in managing large datasets and offers enhanced predictive accuracy compared to baseline models. It effectively addresses the limitations observed in models like LSTM, which often struggle with adequately capturing feature information, and overcomes the generalization weaknesses inherent in models such as the Transformer. This advancement significantly boosts the efficiency of environmental monitoring and fosters both automation and intelligence in the analysis of environmental data.

Assessment on natural ventilation and pollutant dispersion around sunken squares by transient simulation

Sunken square is a semi-open public space that has been gaining popularity in urban planning and designs. Its semi-open design is beneficial to ventilation of the connected underground spaces, but it is also subject to potential exposure to ground-level traffic pollutants. To evaluate the semi-open design’s influence on the balance between underground ventilation efficiency and the pollutant exposure, this study uses large eddy simulation (LES) to simulate turbulent wind flow characteristics and pollutant dispersion in a typical sunken square. The sunken square is connected to two indoor spaces with single-sided opening, and the design features of staircase and arcade are further tested for their influences on the wind flow field. The air change rate per hour (ACH, h−1) is adopted to quantify the ventilation efficiency of the two connected indoor spaces. Results show that the staircases amplify wind velocities for the indoor spaces but also bring higher pollutant concentrations inside together. Moreover, the design of the arcade at the opening prompts the vortex to shift towards the entrance, leading to a heightened concentration of pollutants. Meanwhile, the effective ACH is mostly contributed by the turbulent diffusion (ACHt), while the mean flow (ACHm) has much less effect on the ventilation of the indoor spaces. These findings of this study provide references for sunken square design.

Features of improving the operation of the ventilation system in underground communication structures

This scientific article presents the main results of a study on improving the performance of ventilation systems in underground transport communications. Research is a hot topic, since improving the performance of ventilation systems can significantly improve living conditions and safety of people, as well as reduce negative impacts on the environment. The authors of the article propose several directions for improving the performance of ventilation systems, such as the use of renewable energy sources, heat recovery systems and intelligent ventilation systems based on sensors and algorithms for analyzing and regulating air quality. These recommendations may be useful for creating better underground ventilation systems in various parts of the world. The article also suggests possible directions for future research in this area, such as the development of new technologies and materials, the study

Design of structured meshes of mining excavations based on variability trends of real point clouds from laser scanning for numerical airflow modeling

Various technologies are used to acquire and process 3D data from mining excavations, such as Terrestrial Laser Scanning (TLS), photogrammetry, or Mobile Mapping Systems (MMS) supported by Simultaneous Localization and Mapping (SLAM) algorithms. Due to the often difficult measurement conditions, the data obtained are often incomplete or inaccurate. There are gaps in the point cloud due to objects obscuring the tunnel. Data processing itself is also time-consuming. Point clouds must be cleaned of unnecessary noise and elements. On the other hand, accurate modeling of airflows is an ongoing challenge for the scientific community. Considering the utilization of 3D data for the numerical analysis of airflow in mining excavations using Computational Fluid Dynamics (CFD) tools, this poses a considerable problem, especially the creation of a surface mesh model, which could be further utilized for this application. This paper proposes a method to create a synthetic model based on real data. 3D data from underground mining tunnels captured by a LiDAR sensor are processed employing feature extraction. A uniformly sampled tunnel of given dimensions, point cloud resolution, and cross-sectional shape is created for which obtained features are applied, e.g. general trajectory of the tunnel, shapes of walls, and additional valuable noise for obtaining surfaces of desired roughness. This allows to adjust parameters such as resolution, dimensions, or strengths of features to obtain the best possible representation of a real underground mining excavation geometry. From a perspective of Computational Fluid Dynamics (CFD) simulations of airflow, this approach has the potential to shorten geometry preparation, increase the quality of computational meshes, reduce discretization time, and increase the accuracy of the results obtained, which is of particular importance considering airflow modeling of extensive underground ventilation networks.

Research on Intelligent Control of Regional Air Volume Based on Machine Learning

To address the challenge of intelligently controlling air volume in regions affected by the frequent fluctuations in underground ventilation networks, a remote intelligent air regulation method based on machine learning was presented. This method encompasses three core components: local fan frequency conversion regulation, associated branch air resistance regulation, and a comprehensive integration of both. Leveraging foundational mine ventilation theory, the principles behind branch sensitivity air regulation were dissected. By applying these principles, the key performance indicators crucial for the regulation of air volume within the ventilation system were identified. Subsequently, an intelligent model for regional air volume control was constructed. To validate the approach, an experimental platform for intelligent air volume control was established, guided by geometric, dynamic, and kinematic similarity criteria. Then, the experimental methodologies for simulating various ventilation scenarios were discussed, the data acquisition techniques were introduced, and the obtained results were analyzed. Employing machine learning techniques, we utilized five distinct algorithms to predict the operational parameters of targeted air volume ventilation equipment. It enabled precise and efficient control of air volume within the region. The results indicated that the least squares support vector machine (LS-SVM) stood out by delivering high-precision predictions of target air volume ventilation equipment parameters, all while maintaining a relatively short calculation time. This swift generation of feedback data and corresponding air volume control strategies will contribute to the precise management of air volume in the area. This work served as a valuable theoretical and practical guide for intelligent mining ventilation control.

Optimization and Investigation of Rapid Sealing Technology Based on Mine Disaster Period

Due to the particularity of mine spaces and the limitations of underground ventilation, the gas in disaster areas changes greatly after a fire occurs. Rapid sealing technology is beneficial for preventing the development of fires and gas explosions by controlling oxygen. Using the Fuzzy Analytic Hierarchy Process (FAHP), in this research, we analyzed the three most effective rapid sealing processes, conducted experimental research on the three sealing processes, and developed a further optimized design. At the same time, according to different stages of blasting damage, the change characteristics and migration laws of explosive hazardous gases in a disaster area were analyzed using fluent numerical simulation. Additionally, the ability of the three optimal processes to create an airtight area was measured in this research. The applicable scenarios and scope of the three technologies were found, which provides a wider range of application scenarios and more diverse options for rapid airtightness during catastrophic periods, mine fire prevention, and explosion protection.

Determination of the in situ hydraulic parameters of the Callovo–Oxfordian clay rock in a long-term hydraulic interference testing at Andra's Underground Research Laboratory (CMHM)

Abstract. Between 2009 and 2015, Andra has conducted a unique long-term hydraulic interference test in two parallel boreholes 1 m apart from each other and air core drilled in the undisturbed Oxfordian Clay rock at Andra's Underground Research Laboratory (CMHM) in Bure, France. The experimental set-up consisted of six test intervals positioned along the parallel boreholes drilled from a drift located within the Callovo–Oxfordian clay at around 500 m b.g.l. (below ground level). The 20 m boreholes were oriented around 30∘ downwards. The pressure sensors linked to six intervals of 1 m length each allowed for continuous pressure measurement over 6 years and a slanted borehole for the observation of rock displacements (see Fig. 1). Additionally, flow rates were measured during water injection tests that lasted weeks or months. This extensive set of hydraulic data allowed, for the first time, a precise determination of the in situ Callovo–Oxfordian clay rock permeability and anisotropy and its specific storage at the metre to decametre scale. It was achieved based on an automated calibration, using a 3D flow model and explicitly considering all the relevant hydraulic elements acting on the flow system (such as rock mass, borehole disturbed zone and sealing elements) and the drift acting as a steady sink due to the underground ventilation (see Fig. 2). The history matching was performed on the transient pressure measurements. The obtained numerical calibration results were in close agreement with the hydraulic parameter values of the Callovo–Oxfordian clay determined at a smaller scale (single borehole tests and rock core samples in the laboratory), therefore demonstrating the reliability of the very low permeability of the Callovo–Oxfordian clay at the metre to decametre scale. Furthermore, the modelling illustrated the impact of the measurement set-up and its details on the observed hydraulic behaviour. The analysis methodology and the main findings will be presented.

Embedded religiousness and the Kotosh religious tradition in highland Peru: the site of La Seductora

Religion played a key role in the social organisation and political authority of early Andean societies. Excavations at La Seductora in Peru have identified a circular structure with a central hearth and an underground ventilation shaft. The authors argue that the structure belongs to the Kotosh religious tradition, which dominated the central Andes during the Late Archaic and Formative periods (2800–550 BC). Probably representing a small shrine for use by local families, the authors situate La Seductora within the context of power and religiosity in Andean society, providing a model of relevance to similar contexts elsewhere in the world.

Ventilation optimization through digital transformation

Underground mines require electricity to operate both the main surface fans and auxiliary systems, with primary ventilation systems typically accounting for approximately 40-60% of the mine's overall electricity consumption. The primary reason for this considerable expense is that most underground ventilation systems are designed for peak demand, regardless of the actual demand, which is commonly dictated by diesel equipment usage in trackless mining operations. Most platinum mines on the Great Dyke in Zimbabwe tend to operate their ventilation systems at this peak level, despite the mine's air quantity being well in excess of the 'true' ventilation needs. This is due to a lack of appropriate ventilation controls. The authors designed and installed a ventilation-on-demand system at one of the bord and pillar platinum mines to minimize the use of redundant air in underground operations. Fourth industrial revolution techniques were applied to the environmental monitoring and tracking systems thereby optimizing air quantity demands. The mine managed to reduce its annual power consumption by 23% through the implementation of manual control and time-of-day scheduling levels of the ventilation-on-demand concept. There was also a 6% productivity improvement, mainly attributable to an increased face time as a result of the significant reduction in the re-entry period following a blast. This paper introduces a novel concept of ventilation optimization through digital transformation targeting mainly room and pillar platinum mines. A system was designed, installed, and commissioned, though there is currently an ongoing optimization process to harness the full benefits such as productivity enhancement, reduced power costs, and improved worker health.

Passive ventilation for sustainable underground environments from traditional underground buildings and modern multiscale spaces

Ventilation is the primary means to control the health risks from ‘high heat, humidity and pollution’ in urban underground spaces. Natural ventilation helps reduce the energy and carbon of mechanical ventilation but remains a challenge, especially in high-density cities and global warming. This study aims to explore the potential of passive underground ventilation in high-density modern cities, which contributes to alleviating potential conflicts between health and energy. As a historic and widespread method, passive ventilation improves the climate adaptation and energy efficiency of building forms while introducing natural elements to improve physical and psychological health. This paper reviews the representative cases and studies on passive ventilation in traditional underground buildings and analyses their principles and problems using computational fluid dynamics (CFD) simulations. Further, this paper proposes design highlights and space prototypes for ‘space–airflow’ coupling from multiscale spaces. The design highlights include the following: 1) urban scale: urban wind corridors and downdraught from the ground/overhead; 2) site scale: microclimate and coupling layout between the pressure difference and the air inlet/outlet; 3) building scale: integrated layout of ventilation and functional spaces; and 4) room scale: ventilation mode and efficiency. The CFD results indicate that optimising the layout and form of spaces effectively enhances the natural ventilation. These findings were previously obscured and overlooked in urban design and architectural design. This study helps urban designers, architects, engineers and researchers achieve comfortable and adequate natural ventilation when exploring sustainable underground spaces.

Study on the Influence of the Cage Lifting Piston Effect in Main Intake Shafts on Air Flow in Transportation Lanes

The main intake shaft in the mine serves as the main intake and return air shaft and also serves as a lifting shaft. The piston wind effect caused by the frequent operation of large and efficient hoisting cages in the shaft will disturb the normal flow of airflow in the transport lane connected to the shaft and affect the underground ventilation effect. Therefore, based on the SST k-ω turbulence model, this paper uses the dynamic mesh to simulate the air-fluid in the cage running in the shaft and verifies the simulation data through field measurement to study the influence of piston effect on the airflow field in the transport lane. The results show that the piston effect caused by cage operation in the shaft will disturb the flow of normal airflow in the transportation lane and affect the ventilation effect in the mine. The 1765.0 m transport lane is closest to the position of the shaft inlet, which is most significantly affected by the piston wind effect. The low-speed eddy current zone generated at the tail of the cage in the upwind operation has a large area and strong adsorption force, which causes the gas at the local position in the transportation lane to generate eddy current and reverse flow, hindering the flow of fresh air in the lane. The influence distance and strength of the piston effect on each measuring point in the transportation lane are limited. When the measuring point distance increases from 21.7 m to 71.7 m, the differential pressure of measuring points in 1414.0 m, 1584.0 m and 1765.0 m transport lanes decreases by 11.08 Pa, 9.62 Pa and 8.58 Pa, respectively.

An Efficient Method for Optimizing Sensors’ Layout for Accurate Measurement of Underground Ventilation Networks

An Efficient Method for Optimizing Sensors’ Layout for Accurate Measurement of Underground Ventilation Networks

Modeling and Control of Small-Scale Underground Mine Ventilation Networks

This paper presents a nonlinear model and a control strategy to regulate airflow in small-scale underground mine ventilation networks. In underground ventilation control systems, a sensor and an actuator for each branch are usually considered. However, in small-scale underground mines, it is too expensive to have automatic doors for controlling the air flow in each tunnel, as well as to install flow and gas sensors in each branch. In order to regulate airflow in small-scale underground ventilation networks, the number of sensors and actuators is regarded as a limitation for practical installation. This work presents an alternative modeling of the network, with direct control of the airflow in each tunnel, by varying the speed of the fans available on the external surface of the mine. A state space model is presented, and a linear quadratic controller with integral action and a state estimator is designed. To validate the model and the controller, a network ventilation system for a small-scale mine with nine branches (tunnels) and two actuators (fans) is presented.

Air Quality and Thermal Environment of Primary School Classrooms with Sustainable Structures in Northern Shaanxi, China: A Numerical Study

In northern Shaanxi, China, the air quality and thermal insulation properties of primary school classrooms should be given more attention due to the relatively low temperatures in the winter, which are significant to the learning processes of students in classrooms. Some sustainable building measures have been designed and constructed to improve the air quality and thermal comfort of classrooms in this region; however, is still unclear how these measures influence air quality and temperature. This study investigated the indoor air quality and thermal environment of a typical primary school classroom in Yulin city, Shaanxi Province, China. The classroom was characterized by sustainable structures, including double-sided corridors and an underground ventilation pipe, for better thermal insulation. By conducting on-site monitoring in the classroom and performing various numerical simulations based on finite element software, the variations in the indoor air quality (carbon dioxide, water vapor concentration) and temperature over time, and under different conditions, were investigated. Moreover, influences (i.e., of corridors, ventilation pipes, window areas, classroom areas, and the number of students) on the air quality and temperature were analyzed. It was proven that double-sided corridors, underground ventilation pipes, and windows with heights/widths equaling 1 could provide energy-efficient and livable building structures for primary school classrooms in the northern Shaanxi region of China.

Mathematical Modeling and Optimal Control of Underground Ventilation and Air Conditioning in Station

The underground ventilation and air-conditioning system of the station accounts for about 40% of the total energy consumption of the subway. One of the important reasons is the cooling load of the station. The related control process has typical nonlinear, time-varying, and large inertia characteristics, and the traditional PID control algorithm is difficult to achieve the ideal control effect. Therefore, it is of great significance to study the application of the intelligent algorithm in subway ventilation and air-conditioning control systems to improve the control effect. Based on the analysis of the coupling characteristics of temperature and humidity control in subway air-conditioning systems, this paper designs the feedforward decoupling link according to the identification model and analyzes the control curves with and without the decoupling link when using conventional PID control, which shows the effectiveness of the method proposed in this paper.

Research on the Influence of Natural Wind Pressure in Deep Mines on Ventilation Stability

Deep mines are greatly affected by changes in natural wind pressure because of their large buried depths and long ventilation paths. Changes in natural wind pressure do affect the air flow of the underground ventilation system, and even change the direction of individual branches. If the dynamic changes of natural wind pressure are not monitored constantly, it is very likely to cause disasters such as gas overrun and may even lead to heavy casualties. In this paper, the changes of natural wind pressure and the air volume entering the mine are measured on‐site in the 630 mining area in the south wing of Tangkou Coal Mine, Then, compare the change law of natural wind pressure with the change law of ventilation air volume. Finally, through numerical simulation by FLUENT, the change of internal flow in the gob where there is a loosely closed condition is simulated. Through research, the annual natural wind pressure change and the change of air intake in the 630 mining area of the south wing of Tangkou Coal Mine were obtained; The influence of changes in external conditions on the ventilation air volume of deep mines is obtained; The importance of the influence of natural wind pressure on the stability of the deep mine ventilation system is verified.

A novel design of dehumidifier system in underground pumped storage power station

The heavy water condensation problem has led to safety concern for the workers and electrical facilities in the underground pumped storage power station. As for current dehumidification scheme, heat and humidity load are all removed through the air conditioning unit, which has high energy consumption and low efficiency. As a large amount of moisture comes from the external fresh air, in this study, we set the dehumidification system in the underground ventilation tunnel. By using the air inlet channel to lighten the wet load, the heat and humidity parameters of the fresh air are processed as far as possible in the front of the air supply, so as to achieve the purpose of energy saving operation. In this study, numerical modelling was used to simulate the control scheme of the heat and humidity environment. Compared with the traditional method, the two new dehumidification schemes can take about 1/3 of the wet load of the main workshop, and the dehumidification efficiency is improved. Therefore, this study is expected to be a promising tool for reducing air humidity in underground workshops.

Identification of sources with abnormal radon exhalation rates based on radon concentrations in underground environments

When there is poor ventilation or an irregular radon exhalation rate in an underground environment, it is necessary to judge whether the radon concentration is abnormal. To protect personal safety and health from radon gas, it is necessary to track the location of an abnormal radon source and measure its release rate to formulate emergency control and eradication measures. However, in an underground environment, it is impossible to fully monitor the radon concentration at every location, and as a result, blind spots are present, making it difficult to obtain timely early warnings in the event of an abnormal radon exhalation rate. Based on the distribution of radon concentration in an underground environment, this research establishes a theoretical mathematical model of an underground ventilation network containing radon. We combined particle swarm optimization with the long short-term memory (PSO-LSTM) method, which uses part of a time series signal of monitored radon concentrations to track the location of an abnormal radon source and determine an abnormal radon exhalation rate. Performing experiments of theoretical examples and actual underground ventilation environment examples, we prove the necessity of optimizing the monitoring position of the angle-connected ventilation network. The results show that the PSO-LSTM model based on radon concentration monitoring can process time series signals. Its accuracy and decision coefficient greater that is than 0.9 indicate the reliability of the model and method.

NON-STATIONARY TRANSMISSION OF HEAT AND HYGROSCOPIC MASS BETWEEN VENTIIATION FLOW OF METRO AND SURROUNDING MINING MASSIF

According to modern technologies of construction and operation of transport tunnels, it is assumed in the present work that drainage of water does not occur inside the membrane in the area of reinforced coating of the tunnel and here takes place a non-stationary process of transfer of hygroscopic mass (moisture) together with а similar process of heat transfer between the ventilation stream and the surrounding mining massif. Thus, we have to deal only with the sorption mass content in the pores of the massif and the water in the explicit form in the tunnels can only be in exceptional cases as local sources and therefore, their influence on the ventilation flow should be considered separately. The paper provides results of mathematical modeling of heat and mass transfer processes as well as graphs and nomograms, which can be used to define non-stationary coefficients of the heat and mass transmission required for thermal physics calculation of underground ventilation. The additional flows initiated by the Soret and Dufour effects usually strengthen the main flows, but in practice one can find a case where it is not necessary to take into account the effect of additional flows. Based on the analysis of processes, the criteria that determine the numerical value of these show the case when accounting for additional flows of Soret and Dufour is mandatory. The marked effects can be ignored when 106 Lα=1.