Pillarburst proneness due to large-scale excavations in deep mines (Case study: The Provence coal mine)

The objective of this paper is to examine the applicability of the rockburst proneness criteria by using the numerical modeling tool. Many rockburst criteria are illustrated by the case of a deep coal mine in France, in which pillarburst (RC2) took place in 1993 in the shaft station, which is located at 1000 m from the earth’s surface and it was excavated in 1984 by using the room-andpillar mining method. The shaft station is surrounded by several longwall panels that were exploited between 1984 and 1994. To assess the stress redistribution and the stored strain energy concentration due to mining operations, a detailed large-scale finite difference numerical model of the mine has been constructed. The excavations in the numerical model are performed into two steps. Firstly, the shaft station galleries’ are excavated to determine their effect on the bursted pillar (RC2). Then, the longwall panels are excavated year by year to detect their effect on the shaft station pillars’. The numerical modeling results show that the vertical stress increased on the pillars due to the excavation of the longwall panels. To assess the pillarburst proneness in the shaft station area, the energy-based rockburst criteria (i.e., Loading System Stiffness (LSS)) are found to be more efficient than the stress-based rockburst criteria (i.e., Brittleness coefficient (B))

Pillar burst assessment based on large-scale numerical modeling

International audienceStress concentration is a direct result of stress redistribution around an excavation, that may lead to rock bursting under specific geomechanical conditions. This paper presents a case-study of a rockburst that took place in the shaft station area of the Provence coal mine in Southern France. The mined coal seam has a 2.5 m thickness and a 10° dip angle. The rockburst occurred in 1993 at the shaft station level, where it is surrounded by several longwall panels that were excavated between 1984 and 1994. The area of the shaft station is at 1000 m depth. A very thin layer of stiff limestone occupied the middle of the exploited coal seam. A large-scale finite difference numerical model of the mine has been constructed by using FLAC3D. The model simulates the area of the shaft with its irregular pillars and the longwall panels excavated between 1984 and 1993. The excavations were performed in two steps. Firstly, the galleries of the shaft station area were excavated in order to determine their effect on the failed pillar. Then, the longwall panels were excavated year by year to detect the stress and strain energy increments induced on the pillars. The origin of the rockburst was analysed based on different rockburst criteria. The results show that the vertical stress increased in the shaft station pillars due to excavation of longwall panels. In addition, we found that the small pillars have higher burst tendency than the large ones. Finally, the Burst Potential Index (BPI) was found to be able to estimate the pillar burst tendency based on the energy storage rate (ESR), however, this criterion (BPI) is based on calculating the stress and the energy changes in the vertical direction only

Initialization of highly heterogeneous virgin stress fields within the numerical modeling of large-scale mines

International audienceThe objective of the present paper is to propose a methodology to numerically simulate (i.e., initialize) the pre-mining stress field in complex but rather frequent situations in which the classical overburden-weight assumption and existing stress measurements are in disagreement and where the stresses strongly vary from one zone to another, even at constant depth. This methodology is illustrated by the case of a deep mine in France that exploits a 10°-dipping coal seam, in which numerous stress measurements were carried out. Virgin principal stresses in this mine have been shown to be highly heterogeneous and anisotropic. To correctly reproduce such a challenging initial stress state in a numerical model and to be able to later calculate mining-induced stresses, five distinct methods (M#1 to M#5) are successively presented and compared, along with their advantages and drawbacks. All of them are based on “fixed” boundary conditions, with null normal displacements on all lateral boundaries except on the top one, which is considered as a free surface of the Earth coinciding with the natural flat topography. The initial conditions of the model assume that the pre-mining stress components linearly depend on the Cartesian coordinates x, y and z (depth), and the Simplex Method is used to calculate the linear coefficients by minimizing the squared difference between the measured stresses and their simulated values. We show that the use of 3D stress gradients produces more realistic results than a 1D vertical stress gradient

3D numerical simulation of the goaf due to large-scale longwall mining

International audienceDue to longwall excavations, the upper strata disturb, the roof and the floor of the opening become in contact. This disturbed area is commonly known as the “goaf area”. The challenge of simulating numerically the goaf area is to identify its geometry and its equivalent mechanical properties. The main objective of this study is to improve the 3D numerical simulation of longwall mining and its accompanying goaf area, which will permit us to observe the stress changes due to longwall excavations. The Provence coal mine in the South of France has been chosen to be the case study of the current research, where the mined coal seam has 2.5 m thickness and the average depth of the mine is 1000 m. The longwall panels have a regular width of 200 m and various lengths from 400 up to 1400 m. A large-scale finite difference numerical model of the mine was constructed by using FLAC3D. The numerical modeling of the goaf area was performed in two steps. The first step was to identify the geometry of the goaf area above longwall panels. The second step was to calibrate its equivalent mechanical properties with the total convergence between the roof and the floor. The goaf geometry and the mechanical properties were then calibrated with the in-situ surface subsidence. The results show that applying a linearly varying elastic modulus within the goaf area is a very effective method to express its heterogeneity, which also gave rational surface subsidence values for panels width less than 1000 m. In addition, in terms of stress redistribution, the induced vertical stress increases progressively with panel width, and it becomes close to the initial values at the center of the goaf for panel width larger than 1000 m

The brain selectively tunes to unfamiliar voices during sleep

AbstractThe brain continues to respond selectively to environmental stimuli even during sleep. However, the functional role of such responses, and whether they reflect information processing or rather sensory inhibition is not fully understood.Here, we presented 17 human sleepers (14 females) with their own name and two unfamiliar first names, spoken by either a familiar voice (FV) or an unfamiliar voice (UFV), while recording polysomnography during a full night’s sleep. We detected K-complexes, sleep spindles, and micro-arousals, and then assessed event-related potentials, oscillatory power as well as intertrial phase synchronization in response to the different stimuli presented during non-rapid eye movement (NREM) sleep.We show that UFVs evoke more K-complexes and micro-arousals than FVs. When both stimuli evoke a K-complex, we observed larger evoked potentials, higher oscillatory power in the high beta (&gt;16Hz) frequency range, and stronger time-locking in the delta band (1-4 Hz) in response to UFVs relative to FVs. Crucially, these differences in brain responses disappear when no K-complexes are evoked by the auditory stimuli.Our findings highlight discrepancies in brain responses to auditory stimuli based on their relevance to the sleeper and propose a key role for K-complexes in the modulation of sensory processing during sleep. We argue that such content-specific, dynamic reactivity to external sensory information enables the brain to enter a ‘sentinel processing mode’ in which it engages in the many important processes that are ongoing during sleep while still maintaining the ability to process vital information in the surrounding.Significance statementPrevious research has shown that sensory processing continues during sleep. Here, we studied the capacity of the sleeping brain to extract and process relevant sensory information. We presented sleepers with their own names and unfamiliar names spoken by either a familiar (FV) or an unfamiliar voice (UFV). During non-rapid eye movement (NREM) sleep, UFVs elicited more K-complexes and micro-arousals than FVs. By contrasting stimuli which evoked K-complexes, we demonstrate that UFVs triggered larger evoked potentials, stronger time-locking in the delta (1-4Hz) band, and higher oscillatory power (&gt;16Hz) relative to FVs. These differences in brain responses disappeared when no K-complexes were evoked. Our results suggest a pivotal role for K-complexes in the selective processing of relevant information during NREM sleep.</jats:sec

The Brain Selectively Tunes to Unfamiliar Voices during Sleep

The brain continues to respond selectively to environmental stimuli during sleep. However, the functional role of such responses, and whether they reflect information processing or rather sensory inhibition, is not fully understood. Here, we present 17 human sleepers (14 females) with their own name and two unfamiliar first names, spoken by either a familiar voice (FV) or an unfamiliar voice (UFV), while recording polysomnography during a full night of sleep. We detect K-complexes, sleep spindles, and microarousals, and assess event-related and frequency responses as well as intertrial phase synchronization to the different stimuli presented during nonrapid eye movement (NREM) sleep. We show that UFVs evoke more K-complexes and microarousals than FVs. When both stimuli evoke a K-complex, we observe larger evoked potentials, more precise time-locking of brain responses in the delta band (1–4 Hz), and stronger activity in the high frequency (&gt;16 Hz) range, in response to UFVs relative to FVs. Crucially, these differences in brain responses disappear completely when no K-complexes are evoked by the auditory stimuli. Our findings highlight discrepancies in brain responses to auditory stimuli based on their relevance to the sleeper and propose a key role for K-complexes in the modulation of sensory processing during sleep. We argue that such content-specific, dynamic reactivity to external sensory information enables the brain to enter a sentinel processing mode in which it engages in the important internal processes that are ongoing during sleep while still maintaining the ability to process vital external sensory information.SIGNIFICANCE STATEMENTPrevious research has shown that sensory processing continues during sleep. Here, we studied the capacity of the sleeping brain to extract and process relevant sensory information. We presented sleepers with their own names and unfamiliar names spoken by either an FV or a UFV. During NREM sleep, UFVs elicited more K-complexes and microarousals than FVs. By contrasting stimuli that evoked K-complexes, we demonstrate that UFVs evoked larger, more synchronized brain responses as well as stronger power at high frequencies (&gt;16 Hz) relative to FVs. These differences in brain responses disappeared when no K-complexes were evoked. Our results suggest a pivotal role for K-complexes in the selective processing of relevant information during NREM sleep.</jats:p

Rehearsal initiates systems memory consolidation, sleep makes it last

Rehearsal shifts mnemonic processing from the hippocampus to the posterior parietal cortex, sleep stabilizes the transition.</jats:p