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Rock mass behavior in deep mines: in situ monitoring and numerical modelling
No full textInternational audienceWith the aim of better understanding the mechanical behavior of rocks solicited by underground excavations, the rock mass response to mining was studied based on a comprehensive approach. For this purpose, a deep area of the metal mine of Garpenberg (Sweden) was instrumented with a geophysical and geotechnical monitoring network. In situ monitoring data were analyzed and interpreted considering the specific mining method and the local geological setting. In addition, an advanced 3D elasto-plastic numerical model of the mine was built to better understand the interactions between quasi-static stress changes due to mining and the generation of the induced seismicity. Results show a complex rock mass response, strongly influenced by mining and geological characteristics, both in term of seismic and aseismic phenomena. The case study of Garpenberg also highlights the strong potentiality of the proposed approach, which can help improving the seismic hazard assessment in deep mining operations
Automatic full wave-form based monitoring at the deep Garpenberg metal mine
No full textInternational audienceSeveral recent studies demonstrate the high value of array and full wave-form based automatic detection and location approaches for monitoring purposes of natural and induced seismicity. The main benefit of these approaches is generally the significant improvement in detection capacity and relative event location accuracy which improves significance of statistical analysis aiming at identifying changes of the seismic rate in space and time and nucleation phases of potential larger dynamic ruptures. In mines, the implementation of such approaches remains challenging and is today by far nonstandard but would probably significantly help to anticipate destructive rockburst events. Main challenges for usage of these methods are related to the presence of a wide range of seismic noises related to mining activities with often similar signatures as microseismic events. In addition, high sampling frequencies of seismic data (several kHz) used in these environments pose problems for real-time data transfer and processing. Here, we propose an adapted, full-waveform based automatic processing workflow for a local Ineris seismic network located at the deepest levels (> 1 km depth) of the Lappberget district of the Garpenberg metal mine (Sweden). To deal with high frequency sampling (8 kHz) we designed a pre-processing step based on a multi-frequency detection scheme and first-order amplitudebased location. Final source location is then obtained by applying an array coherency based backprojection approach (BacktrackBB) on the preselected and reduced data set. We estimate that detection capacity compared to a usual triggered monitoring system is increased by at least a factor 100. The approach is currently implemented and tested on the local monitoring system and is continuously improved to assure reliable automatic event classification. A second main field of current ongoing investigations focuses on the design and implementation of an automatic “wave form matching” based approach of seismic repeater families. The approach aims at measuring indirectly aseismic slip in the mining area and providing criteria for seismic hazard as asperity density and larger dynamic rupture potential. Indeed, recent results from source mechanism and parameter analysis, relocation and spatio-temporal statistics have shown that seismicity at Lappberget district seems to be dominated by seismic repeater occurrences that can be interpreted as seismic asperities that repetitively rupture (over periods of weeks to years) as a result of loading of the surrounding creeping weak rockmass (e.g. occurrences of talc) initiated from specific production blasts
Pillarburst proneness due to large-scale excavations in deep mines (Case study: The Provence coal mine)
No full textInternational audienceThe 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))
A coupled hydro-mechanical modeling of internal erosion around shield tunnel
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Retour d’expérience international. Accidents significatifs survenus en 2018
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Air quality challenge : measurement and modelling tools for a better management
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Retour d’expérience et facteurs d’influence des données de bioaccessibilité orale des métaux dans les sols
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Overview of the ACMCC Particulate Organonitrates (pON) Experiment
No full textInternational audienceParticulate organonitrates (pON) account for significant fraction of total OA in ambient air. They are formed from the reactions of volatile organic compounds (VOCs) with atmospheric oxidants (OH/NO3 radicals) and NOx. Their quantification can be achieved using aerosol mass spectrometry (AMS), based on the characteristic mass fragment ratio (NO2+/NO+) allowing the distinction from inorganic nitrate. However, the accuracy of the low-resolution aerosol chemical speciation monitor (ACSM) to determine pON has not yet been evaluated. At the Aerosol Chemical Monitor Calibration Centre (ACMCC), an intercomparison for the measurements of pON has been performed in order to obtain a stable and constant generation of pON, so to compare simultaneously the response of nine different AMS/ACSM systems (long-TOF-AMS vs ACSMs; Quads vs TOFs; standard vs capture vaporizers), as well as to investigate the pON physical properties and chemical composition. pON were generated in a Potential Aerosol Mass (PAM) oxidation flow reactor from the reaction of NO3 radical, produced on demand (O3 + NO2), with single VOC precursors. Two biogenic (limonene and b-pinene) and two anthropogenic (acenaphthylene and guaiacol) pON precursors were investigated. For the determination of AMS/ACSM relative ionization efficiencies (RIE), a particle size and mass selection were achieved by combining an aerodynamic aerosol classifier (AAC) and centrifugal a particle mass analyser (CPMA). pON size distribution and total particle number concentration were monitored by a scanning mobility particle sizer (SMPS) and a condensation particle counter (CPC) allowing the characterization of the pON density. In order to get insights into the pON optical properties, as well as their chemical composition and formation processes, measurements also included cavity-enhanced absorption spectroscopy (NO3 radical by IBB-CEAS), proton-transfer-reaction MS (PTR-MS), multi-wavelengths aethalometer (AE33), as well as filter samplings for further high-resolution MS off line analyses (GC and LC/Q-TOF-MS). An overview of the set-up and the experiments performed will be presented together with preliminary key results. This work is part of the European COST Action CA16109 COLOSSAL and the H2020 ACTRIS-2 project (grant agreements n° 654109)
Les "métriques" du risque
No full textInternational audienceDans cet article, on redéfinit ce qu’est un “risque” puis à partir de cela, on décrit les moyens de mesure (“métrique”) les plus adaptés pour évaluer le risque. On s’aperçoit que la métrique depend beaucoup de la nature du risque (économique, industriel, technologique, opérationnel,…). On montre en particulier que le risque procédé ne semble pas correctement couvert par les métriques disponibles connexes (risques technologique et opérationnel) et on propose une méthode pour combler ce manque. Une illustration est proposée sur la base d’un cas pratique. Pour l’auteur, lui même responsable sécurité et enseignant en génie des procédés, ce qui est proposé pourrait correspondre à la definition d’une “ingénierie de la sécurité”
