Microseismic monitoring and stability evaluation for the large scale underground caverns at the Houziyan hydropower station in Southwest China

    Microseismic Monitoring and Stability Evaluation for the Large Scale Underground Caverns at the Houziyan Hydropower Station in Southwest China N.W. Xu, T.B. Li, F. Dai, B. Li, Y.G. Zhu, D.S. Yang PII: DOI: Reference:

S0013-7952(15)00031-9 doi: 10.1016/j.enggeo.2015.01.020 ENGEO 3971

To appear in:

Engineering Geology

Received date: Revised date: Accepted date:

7 May 2014 13 January 2015 19 January 2015

Please cite this article as: Xu, N.W., Li, T.B., Dai, F., Li, B., Zhu, Y.G., Yang, D.S., Microseismic Monitoring and Stability Evaluation for the Large Scale Underground Caverns at the Houziyan Hydropower Station in Southwest China, Engineering Geology (2015), doi: 10.1016/j.enggeo.2015.01.020

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ACCEPTED MANUSCRIPT Microseismic Monitoring and Stability Evaluation for the Large Scale Underground Caverns at the Houziyan Hydropower Station

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in Southwest China

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N.W. Xu1, 2, T.B. Li2, F. Dai 1*, B. Li1, Y.G. Zhu3, D.S.Yang4

1 State Key Laboratory of Hydraulics and Mountain River Engineering, College of Water Resource and Hydropower, Sichuan University, Chengdu, Sichuan Province 610065, P.R.

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China

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2 State Key Laboratory of Geo-Hazard Prevention and Geo-Environment Protection, Chengdu University of Technology, Chengdu, Sichuan Province 610059, P.R. China

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3 China Guodian Dadu River Houziyan Hydropower Development Co., Ltd., Kangding,

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Sichuan Province 610041, P.R. China

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4 State Key Laboratory of Geomechanics and Geotechnical Engineering, Institute of Rock

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and Soil Mechanics, Chinese Academy of Sciences, Wuhan, Hubei Province 430070, P.R.

* Corresponding author

China

Tel.: +86 28 8540 6701;

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Email: [email protected]

ACCEPTED MANUSCRIPT Abstract: The stability of underground caverns and the excavatability of rock masses are important

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for geotechnical engineering practices during the design and construction stages. The risks

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associated with underground caverns at the Houziyan hydropower station in Southwest China

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are growing due to excavation-induced unloading. To assess the instability of underground caverns and resolve the complex subsurface conditions of the highly fractured rock mass, a high-resolution microseismic monitoring system was established in deep underground caverns.

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This system was used to determine the relationship between the measured microseismic activities and the excavation damage zones of the surrounding rock mass. The excavation

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damage zones and potential risk regions in the underground caverns were identified by analyzing the tempo-spatial distribution of microseismic activities. In addition, the correlation

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between microseismic activities and pre-existing geological structures was determined, and

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traditional monitoring results were analyzed. To validate the correlation between seismicity and the excavation damaged zones of the underground caverns, a numerical model was

monitoring

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employed to further evaluate the deformation and stability of the surrounding rock mass. The results

demonstrate

that

microseismic

events

mainly

occurred

in

high-stress-concentration regions, corresponding with the results obtained from the numerical

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analysis. Therefore, this comprehensive method, which incorporates microseismic monitoring, numerical analysis, traditional monitoring and field observations, is promising for predicting the deformation and instability of surrounding rock masses in the underground caverns subjected to excavation.

Keywords: Underground group caverns; Stability evaluation; Microseismic monitoring; Numerical simulation; Houziyan hydropower station

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ACCEPTED MANUSCRIPT 1. Introduction Myriads of large-scale, deep underground powerhouses for large hydropower stations are

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being constructed or are currently in the design and planning stages in Southwest China. The

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stability of the surrounding rock mass in underground caverns plays an important role in

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engineering safety (Li et al., 2014a). The effective prediction and control of the stability of underground caverns is important for ensuring the engineering safety of these projects.

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Numerous studies have been conducted to investigate the behaviors of the surrounding rock mass and the stability of underground caverns subjected to excavation activities. In

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recent decades, computer methods have become increasingly popular for investigating the stability of underground caverns. For example, Feng et al. (2011) proposed an intelligent and dynamic design method for the stability analysis of large cavern groups that focused on the

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characteristics of strong excavation unloading of the high sidewalls of multi-cavern group.

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Cai et al. (2007) investigated the acoustic emissions (AE) activities in large-scale

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underground excavations using a coupled FLAC/PFC method. Zhu et al. (2008, 2010) predicted the sidewall displacement and evaluated the stability of typical underground caverns. Sitharam and Latha (2002) proposed new mechanical models for the surrounding rock mass

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of caverns in jointed rock masses. Yazdani et al. (2012) conducted displacement-based numerical back analysis to estimate rock mass parameters in the Siah Bisheh powerhouse cavern using continuum and discontinuum approaches. Park et al. (2013) determined the numerical analysis-based shape design of underground rock caverns. Wu et al. (2010) and Zhou et al. (2012) studied unloading deformation and different crack sizes for the surrounding rock masses of underground caverns at the Jinping I hydropower station. Aydan et al. (2010) studied the dynamic response and stability of underground structures during earthquakes. Yoshida and Horii (2004), Tezuka and Seoka (2003), and Dhawan et al. (2004) analyzed the stability of the surrounding rock mass on specific hydroelectric projects using the finite element and discrete element methods. These studies significantly improved our understanding of the damage mechanisms of surrounding rock masses and the stability evaluation of underground group caverns. 3

ACCEPTED MANUSCRIPT To understand and validate the numerical simulation results, in-situ measurements were often used to monitor the deformation of the surrounding rock mass under excavation (Li et al., 2008). The extensive uses of measurement technologies (e.g., global positioning system,

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multiple position extensometers, convergence meters and surface subsidence monitoring) are

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for detecting the surface deformation of underground caverns. However, these techniques

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cannot adequately monitor the inner microcrackings of rocks, which occur preferentially to the macroscopic deformation/failure (i.e., spalling, bulking and rockburst) of surrounding rock masses. In fact, detectable acoustic or seismic signals are always emitted when rocks crack. If

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these signals can be sufficiently recorded as seismograms, the original time, location, and source parameters of the seismic event can be obtained (Cai et al., 2001). Thus, the

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microseismic (MS) monitoring technique can be used to monitor and analyze the surrounding rock mass of underground caverns subjected to excavation-induced unloading (Xu et al.,

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2011b, 2012a).

With the rapid development and application of MS monitoring techniques, many

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achievements have been made regarding our understanding of rock slopes (Lynch et al., 2005; Xu et al., 2011b, 2012a, 2014a), underground mining (Ge, 2005; Wang and Ge, 2008; Lesniak and Isakow, 2009; Kaiser et al., 2009; Trifu and Shumila, 2010; Young et al., 2004; Liu et al.,

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2013; Hudyma and Potvin, 2010; Lu et al., 2013), deep tunnels (Cai et al., 2001; Tang et al., 2011; Hirata et al., 2007; Feng et al., 2012) and the generation of electricity by hot dry rocks (Tezuka and Niitsuma, 2000). For example, Lynch et al. (2005) investigated the engineering application of MS monitoring technique in two case studies and showed that the surface movements inferred from the MS data were spatially correlated with the actual surface movements. Moreover, these authors showed that MS data can be routinely used to understand the effects of mining, and provide accurate assessments of slopes stability. Hudyma and Potvin (2010) proposed an engineering approach for seismic risk management in hard rock mines. Using the MS monitoring technique, Xu et al. (2011b, 2012a, 2014a) analyzed and evaluated the stability of high rock slopes at large-scale hydropower stations in Southwest China, and identified the rock mass failure zones and sliding surfaces of rock slopes. Lu et al. (2013) revealed the MS effects and frequency-spectrum evolutionary rules 4

ACCEPTED MANUSCRIPT before and after rockbursting induced by roof falls based on the deformation of small-scale combined coal and rock samples in failure experiments and in-situ measurements in a strong, burst-prone coal mine. Cai et al. (2001) quantified the rock mass damage in underground

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excavations from microseismic events that were monitored at the Mine-by test tunnel of

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Canada Atomic Energy Limited Company. Tang et al. (2011), Hirata et al. (2007) and Feng et

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al. (2012) investigated and predicted the mechanisms of rockbursts in deep-buried tunnels based on AE/MS activities. Despite all of these studies involving mine field stress, slope instability, hydrofracturing and rockburst hazards, the MS monitoring technique has rarely

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been used to evaluate the stability of deep-buried underground powerhouses subjected to

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excavation.

In this study, the MS monitoring technique was used to evaluate the stability of

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deep-buried underground powerhouses at the Houziyan hydropower station. The Houziyan

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hydropower station, one of the largest hydropower projects, is currently being developed at the Daduhe River, in Southwest China. Three large-scale underground caverns are being

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excavated at the right bank slope. During the excavation of the underground group caverns, rock spalling and rockbursts frequently occurred, which severely affected the construction schedule and worker safety. In addition to traditional monitoring approaches, a

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high-resolution MS monitoring system was used to determine the relationships between the measured MS activities and the excavation damage zones (EDZs) of the surrounding rock mass. By analyzing the MS activities, the EDZ and potential risk regions in the underground caverns were delineated and the correlation between the MS activity, the pre-existing geological structures and the traditional monitoring data were determined. Furthermore, a numerical model was incorporated into the Realistic Failure Process Analysis (RFPA) code to evaluate the deformation and stabilities of the surrounding rock masses.

2. Project description 2.1. Underground powerhouse layout The Houziyan hydropower station is a large-scale step hydropower project recently

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ACCEPTED MANUSCRIPT constructed on the Daduhe River and is located approximately 450 km southwest of Chengdu in Sichuan Province China (see Fig.1). The large-scale underground powerhouse cavern group at the Houziyan hydropower station mainly includes diversion tunnels, the main powerhouse,

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omnibus bar caves (tunnels that connect the omnibus bars of each set with the main

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transformer), the main transformer chamber, the tailrace surge chamber and tailrace tunnels.

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Three main caverns (the main powerhouse, the transformer chamber and the tailrace surge chamber) are arranged in parallel below the ground surface. The powerhouse caverns are mainly buried horizontally at depths of 280 m to 510 m and vertically at depths of 400 m to

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660 m. The minimum vertical and horizontal depths of the main powerhouse are approximately 380 m and 250 m, respectively. The excavation dimensions of the main

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powerhouse are 219.50 m in length, 29.20 m in width, and 68.70 m in height. Thus, this underground powerhouse is one of the largest in China with high sidewalls and long spans.

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The dimensions of the main transformer chamber are 141.10 m in length, 18.80 m in width,

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and 25.20 m in height. Those of the downstream surge-chambers are 60.00 m in length, 23.50 m in width, and 73.98 m in height. The horizontal distance between the center lines of the

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tailrace surge chamber and the crown of the main powerhouse is 134.90 m. The thickness of the rock pillars between the main transformer chamber and the main powerhouse is 45.0 m, and the thickness between the main transformer chamber and the tailrace surge chamber is

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44.75 m (Cheng et al., 2014). A 3D layout of the underground powerhouse caverns of the hydropower station is shown in Fig.2. 2.2. Geological conditions The hydropower station is located in a mountain valley area with steep valley terrain on both sides. The heights of the slopes near the valley are more than 800 m, and the topographic slope is typically 60°~65° below 1,900 m at the left bank slope and 30°~40° above 1,900 m. In addition, the topographic slope is usually 55°~60° below 2,000 m at the right bank slope and 40°~50° above 2,000 m. The bedrock slope of the right bank slope, where the underground powerhouse systems are located, is exposed. A typical geological section of the left and right bank slopes is shown in Fig.3. Due to detailed engineering geological explorations, no regional fractures occur in the area of the powerhouse cavern. Only one fault 6

ACCEPTED MANUSCRIPT (F1-1) occurs that passes through the upstream area of the main powerhouse with a width of 1.0 m to 1.5 m, and its attitude is N60oE/NW∠85o. The other structural planes include secondary small faults, compression-crushed zones and joint fissures. The rock mass at the

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underground powerhouse is relatively intact, and the surrounding rock masses are generally of

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intermediate quality. The hydropower cavern was constructed using a conventional drill and

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blast method. The main powerhouse, transformer chamber and tailrace surge chamber were excavated using 9 benches, 3 benches and 11 benches, respectively. The specific stratified excavation scheme of the underground group caverns is shown in Fig.4. The construction

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schedules for the three main caverns were from November 1, 2011, to May 2014, March 9, 2012, to April 5, 2013, and May 30, 2012, to December 2014, respectively. Currently, the

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transformer chamber is completed, and the C7 bench of the main powerhouse and the T8 bench of the tailrace surge chamber are being constructed as shown in Fig.4 (Cheng et al.,

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2014). Furthermore, a typical geological cross-section of the underground group cavern along

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the center line of 2# omnibus bar cave (Stake 0+51.3) is shown in Fig.5. In this cross-section, the faults (i.e., g1-4-7, g1-4-8, g1-4-15, g1-4-14, f1-4-6 and g1-4-18) exist along the

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surrounding rock mass between the main powerhouse and transformer chamber, demonstrating that the stability of the underground group cavern at the cross-section is controlled by such faults. A stereographic projection of the faults is illustrated in Fig.6 to

structures.

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enable a thorough analysis of the correlations between the faults and the underground

2.3. In-situ stress conditions The characteristics of the tectonic movement at the Houziyan hydropower station included intermittent strong uplift. The direction of the maximum principal stress was approximately EW or NWW~SEE. The rock mass at the underground caverns is given priority over hard and relatively complete metamorphic limestone, which has a relatively high in-situ stress value. To better understand the in-situ stress orientation and magnitude for the underground powerhouse design, 6 groups of in-situ stress measurements were conducted at the right bank slope (see Fig.7). At a horizontal depth of approximately 250 m in SPD1-1 and SPD9-1 (geological exploration tunnels, which were excavated from the surface of the right 7

ACCEPTED MANUSCRIPT bank slope before constructing the underground caverns), both of the maximum principal stresses were 21.5 MPa. In addition, the corresponding directions were N44.3°W and N73.8°W, respectively, and the slopes slant toward the mountains outside of the downstream

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area with dip angles of 21.5° and 47.1°, respectively. At a horizontal depth of 385 m in

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SPD1-5, the maximum principal stress was 36.4 MPa, and the corresponding directions were

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N40.7°W, and slanted toward the mountains outside of the downstream area with a dip angle of 44.5°. At a horizontal depth of 400 m in SPD1-2 and SPD1-3, the maximum principal stresses were 29.1 MPa and 28.1 MPa, respectively. In addition, the corresponding directions

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were N69.9°W and N54.5°W and slanted toward the mountains outside the downstream area with dip angles of 42.5° and 47.5°, respectively. At the horizontal depth of 525 m in SPD1-4,

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the maximum principal stress was 33.5 MPa. In addition, the corresponding directions were N74.7°W, and slanted toward the mountains outside of the downstream area with a dip angle

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of 54.3°. Detailed parameters of the in-situ stress measurements are presented in Table.1. In

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particular, at a horizontal depth of 385 m in SPD1-5, where the stress concentration belt exists, flaking off and spalling of rocks occurred at the tunnel surface. Disk-like rock cores from

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in-situ stress drilling and rib spalling in the underground caverns are shown in Fig.8.

The above testing results show that the geo-stresses at the right bank slope belong to

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high ground stress, because the horizontal depth is greater than 250 m. The direction of the maximum principal stress at the dam site zone is similar to the direction of the regional tectonic principal compressive stress. The in-situ stress increases as the horizontal depth increases, with the local stress concentration belts (Cheng et al., 2014).

Table.1 The results of rock mass in-situ stress measurements in geological exploration tunnels Measuring points

Measuring point locations

1

σSPD1-1

Stake 0+253m in SPD1

253

390

2

σSPD1-2

Stake 0＋ 400m in SPD1

400

560

No.

Horizontal depth/m

Vertical depth/m

Lithology Deep-bed metamorphic limestone Deep-bed metamorphic limestone

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Value(MPa) α(°) β(°) Value(MPa) α(°) β(°)

σ1

σ2

σ3

21.5 315.7 21.5 29.1 290.1 42.5

12.1 147.6 68.0 18.4 15.6 -4.9

7.0 47.3 4.1 13.9 100.3 47.1

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Stake 0＋ 250m in SPD9

576

250

47.5

-12.8

39.7

Value(MPa) α(°) β(°) Value(MPa) α(°)

33.5 285.3 54.3 36.4 319.3

22.6 352.9 -15.3 29.8 3.3

14.1 73.3 31.4 22.3 74.7

β(°)

44.5

-36.2

23.6

Value(MPa) α(°) β(°)

21.5 286.2 47.1

17.6 96.7 42.5

6.2 11.1 -4.8

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β(°)

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385

medium bed metamorphic limestone

16.1 100.4

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780

metamorphic limestone

440

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σSPD9-1

525

22.9 21.2

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Note: α is the angle of the principal stress in the horizontal projection. The angle of true north is zero and clockwise rotation. While β is the dip angle of the principal stress, and the angle of elevation is positive.

3. Microseismic activity characteristics subjected to excavation

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σSPD1-5

Stake 0＋ 236m in the fourth adit of SPD1

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28.1 305.5

3.1 Microseismic monitoring principle

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5

σSPD1-4

Stake 0＋ 525m in SPD1

400

Value(MPa) α(°)

The initiation and growth of stress-induced cracks or fractures denote rock damage and

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4

σSPD1-3

Thin~ medium bed metamorphic limestone Deep-bed metamorphic limestone

emit detectable acoustic or seismic signals (Cai et al., 2001). These signals can be captured as seismograms based on the number of sensors and the time, location, energy release and scalar seismic moment magnitude of each routinely estimated MS event. In rock engineering

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3

Stake 0＋ 106m in the lower adit of SPD1

practices, microcrackings can be identified using seismic monitoring system, and the local damage can be determined by analyzing different seismic parameters, such as time, location, energy release and the moment magnitude. Once a sufficient number of seismic events are recorded and processed, the changes in the strain or stress of the rock mass associated with microseismicity can be quantified (Xu et al., 2011b). Thus, the rock mass failure and potential damage zones in underground group caverns can be predicted and identified. Generally, MS monitoring studies include the followings: (1) counting the number of MS events with a correlation between the microseismicity rate and accumulated energy release; (2) hypocenter positioning of the MS events; (3) analysis of full waveform data; and (4) identifying and determining the potential fracture regions and sliding surface of the underground group caverns from the seismic data during the excavation period (Xu et al., 2011b). 9

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Microcrackings can occur inside the rock mass before the apparent surface deformation appears; the MS events can thus be used as indicators of rock fracturing or damage when the

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rock is approaching failure and the excavation-induced rock mass damage can be located and

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evaluated in underground group caverns. Microseismic mechanism associated with unloading

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processes in underground caverns can be investigated to determine the stability of the surrounding rock mass in underground engineering projects (Cai et al., 2007; Zhao et al., 2013). In addition, compared with traditional measuring technologies, MS monitoring is a

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remote, three-dimensional and real-time monitoring technique. Indeed, the MS event counts, the MS event count rates scaled with the stress–strain relationship and the source location of

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the seismic events are frequently used by researchers to study rock mass failure characteristics under different loading conditions (Cai et al., 2007; Young et al., 2004; Xu et al., 2011b,

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2012a, 2014a). Some waveform parameters involved in the generation of seismic source

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location (e.g., ring-down count, energy, peak amplitude, rise-time and event duration) provide useful information for further investigating rock fracture mechanisms that lead to

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macroscopic deformation and failure.

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3.2 Microseismic monitoring system configuration A high-resolution MS monitoring system manufactured by ESG (Engineering Seismology Group, Canada), was installed in the underground group caverns to monitor the excavation-induced seismicity in the deep rock mass. The monitoring system consists of a Hyperion digital signal processing system, a Paladin digital signal acquisition system, and 18-channel accelerometers (one triaxial accelerometer S8 and 15 uniaxial accelerometers S1-S7 and S9-16, as shown in Fig.9). The accelerometers, which have a frequency response from 50 Hz to 5 kHz (±3 dB) were grouted at the end of diamond-drilled boreholes in the sidewalls of the service tunnels. The seismic array was designed for focal sphere coverage with a source location accuracy of approximately 5 m, when manual processing was used. Overall, the 18-channel seismic monitoring system can cover the crown, upstream and downstream zones of the main powerhouse and the middle wall between the main 10

ACCEPTED MANUSCRIPT powerhouse and transformer chamber. The sensor array located at three different elevations can be used to monitor excavation-induced micro-fracturing in real time. The seismic parameters, such as time, location, magnitude, and release energy are automatically calculated

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and determined by the system. The seismic data are typically processed manually for the

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high-precision seismic location. The sensor array (Fig.9) is set up based on theoretical

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analysis and field observations (Xu et al., 2011a). The 9 uniaxial accelerometers (S1-S6, S11-S13) were placed in the first layer of the drainage tunnels, which are located at the upstream and downstream of the main powerhouse, and at the upstream of tailrace surge

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chamber, respectively. Other sensors were distributed in the rock mass between the main powerhouse and main transformer chamber. The 18-channel sensors were connected to three

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substations (namely, the Paladin acquisition unit) using copper twisted-pair cables. The three substations were connected in series to the central system (namely, the Hyperion digital signal

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processing unit) using optical fiber optics and network cables. The seismic monitoring system

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is typically configured using twisted pair, fiber optics, and network cables or a combination of these cables. Due to geological limitations in the underground group caverns, no GPS signal

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can be used as a time source; therefore, the Paladin units rely on a pulse per second (PPS) signal from the Paladin Timing Source over the network. This method allows the data from each Paladin to be accurately time-stamped, to ensure that multiple units are synchronized

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(Urbancic and Trifu, 2000; Xu et al., 2011b). Furthermore, on-site fixed-point blasting tests and sensors tap tests were performed to verify the positioning accuracy of the seismic monitoring system. The seismic source location error was less than 5 m in the scope of the sensor array and had a high positioning accuracy.

The Hyperion processing system was used to digitize the seismic data with a sampling frequency of 10 KHz and was used to perform preliminary event detection when the recorded signals of the substations exceed a given threshold using the Short Time Average vs. Long Time Average algorithm (STA/LTA). Next, the seismic system was used to calculate a preliminary hypocenter in real time with a homogeneous velocity model and to record the data. Constant P- and S-wave velocities were initially estimated from a joint investigation of on-site blasting tests and digital sound wave tests. The calibrated results indicate that 11

ACCEPTED MANUSCRIPT Vp=5,239 m/s and Vs=3,025 m/s. The seismic source location resulted in the arrival of the P-wave at sensors 5-18 first (often more than 6) and the arrival of the S-wave at 1/4-1/2 on the Simplex algorithm using a L1 norm minimization of time residuals. Additional details can be

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found in the literatures (Trifu and Shumila, 2010; Urbancic and Trifu, 2000; Xu et al., 2011b).

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Typical waveforms for a standard MS event occurring in the underground caverns of the

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Houziyan hydropower station are shown in Fig.10. The traces can be used to evaluate the size and location of the event (Urbancic and Trifu, 1996; Xu et al., 2014a).

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3.3 Temporal and spatial distribution of the microseismicity

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To achieve meaningful results when analyzing the seismic events, the real-time seismogram data must be continuously and accurately recorded. A large number of events, including MS events, production blasts, and some noises subjected to different constructions

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and machineries, were captured. More than 5,000 seismic events were recorded from April 12,

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2013 to February 28, 2014 within a given volume of interest after filtering out the noisy events. Nearly 25% of the database was rejected because it corresponded to the signals of

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blasting events, mechanical vibrations and background noise. The moment magnitude of the processed seismic events ranged from -2.5 to 1.5 during the selected period. Using the

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tempo-spatial distribution evolution characteristics of microseismicity, the present study aimed to forecast the deformation of the surrounding rock mass and to identify the excavation-induced damage zones. Because the working faces gradually moved down with the excavation of the underground group caverns, the accumulation of MS events during this period cannot accurately reflect the damage of the surrounding rock mass subjected to excavation-induced unloading. Therefore, typical periods during which the microseismicity frequency or the spatial distribution of the seismic source locations highlighted were selected for further analysis.

Fig.11 illustrates the rate graph of MS events between April 12 and July 11, 2013. There were 0 to 72 events per day, including small bursting activities. In addition, there were approximately 20 seismic events per day on average. The corresponding spatial distribution 12

ACCEPTED MANUSCRIPT and density contours of the microseismicity recorded during this selected period are shown in Fig.12a, b. Clustering seismic events mainly occur in zones I, II and III. Among these zones, the seismic events clustered at zone I were located near the Stake 0+116.3 m transverse

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section of the upstream sidewall in the main powerhouse. In addition, the seismic events

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clustered at zone II were located near the Stake 0+020.0 m transverse section of the upstream

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sidewall in the main powerhouse, and the seismic events clustered at zone III were mainly located near the 1# and 2# omnibus bar caves of the downstream sidewall in the main powerhouse. The main powerhouse was excavated at the C4 bench between April 12 and July

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11, 2013. The thickness of the C4 bench is 8 m, with an elevation of 1,702.0 m to 1,694.0 m, as shown in Fig.4. Moreover, the 1# and 2# omnibus bar caves were excavated during the

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selected time (between April 12 and July 11, 2013). When combining the field observations and different construction situations, the clustering of seismic events was deduced to mainly

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result from the excavation of the main powerhouse and the omnibus bar caves, because

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damage phenomena, such as cracks, faulting, shotcrete cracking and rock mass fracturing, were common in the sidewalls of the main powerhouse, especially at the rock anchor beams

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(Fig.12c). The corresponding photographs of the surrounding rock mass damage induced by excavation are illustrated in Fig.12c near the MS event concentration zones I, II, and III. In addition, the MS events with a moment magnitude greater than 0 during the selected period

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between April 12 and July 11, 2013 are illustrated in Fig.13 to reveal the correlation between MS events and underground structures. However, the spatial distributions of these large seismic events are largely discrete.

The MS event frequency (see the red five-pointed star in Fig.11) increased on May 19, 2013. Several interpretations were considered to determine what caused this increase in the MS event frequency and how the surrounding rock mass responded to the clustered seismic events. Fig.14 shows the spatial distribution of the MS events during the jumping period between May 16 and May 21, 2013; Fig.15 illustrates the corresponding density contours of the MS events. Nearly 80% of the MS events during the selected period were clustered near the first layer drainage tunnel directly above the 2# and 3# omnibus bar caves. This finding demonstrates that clear rock mass damage should occur in the MS events concentration region. 13

ACCEPTED MANUSCRIPT In addition, shotcrete fractures and spalling occurred at the sidewall of the 2# omnibus bar cave, as shown in Fig.16 (zones I, II and III). Combined with the on-site construction conditions, the 2# omnibus bar cave was excavated exactly during the jump period. Therefore,

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the dynamic construction state is easily revealed by the accumulation of MS events. Moreover,

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rib spalling of the sidewall occurred in the first layer drainage tunnel (Fig.12c), demonstrating

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that the MS event concentration resulted from excavation. Indeed, a joint investigation of the MS activities, excavation conditions and on-site observations can be used to delineate the excavation-induced damage zones. Some guidelines can thus be provided for the next

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excavation and support.

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3.4 Correlation analysis between the microseismicity and geological structures The clear aggregation of the MS events was captured through a seismic monitoring

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system at the area of interest in underground group caverns during the selected period from

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November 1, 2013 and January 14, 2014. Fig.17 shows the occurrence of seismic events near the middle separated wall between the main powerhouse and transformer chamber. Fig.18

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shows the corresponding density contour of the seismic dataset during this period, highlighting the relationships between the spatial distribution of the MS events and the

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geological structure elements. The concentration of MS events was clearly stripped as a potential sliding surface, matching the fault strikes of g1-4-14 and g1-4-15 (Fig.5). The excavation of the transformer chamber was completed during the selected period from November 1, 2013 to January 14, 2014. In addition, the C7 bench of the main powerhouse was in progress (Fig.4), and the footwalls of g1-4-14 and g1-4-15 faults were exposed. Shotcrete cracks and spalling were observed nearby the footwalls of faults g1-4-14 and g1-4-15, as shown in Fig.19. Thus, two rows of pre-stressed anchor cables were added to support the downstream sidewall of the main powerhouse. Therefore, the aggregation of MS events (Fig.17) resulted from rock mass unloading and did not directly result from blasting excavation. The excavation of the C7 bench of the main powerhouse was considered to cause stress mitigation and unloading of the upper rock mass at the middle separated wall, resulting in the activation of the related faults. However, additional MS events would gradually become 14

ACCEPTED MANUSCRIPT concentrated at the studied area as the lower rock mass in the main powerhouse is excavated, if supporting measures are not be implemented in time. In fact, the activation of geological

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initiation, propagation and coalescence of cracks from MS events.

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structures inside underground engineering can be identified by dynamically monitoring the

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3.5 Correlation analysis between microseismic monitoring and traditional monitoring The spatial distribution of the MS events recorded between May 24 and June 1, 2013

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were selected to compare the MS monitoring and traditional monitoring results. During this period, surface deformation occurred at the upstream sidewall of the main powerhouse.

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Furthermore, the upstream sidewall deformation was predicted using the precursor of the MS events recorded in time.

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Fig.20 shows the occurrence of the MS events and the corresponding density contour at

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the upstream sidewall of the main powerhouse from May 24 to June 1, 2013. The MS events were mainly located near Stake 116.30 m (along the Y axis). To further analyze the correlation

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between the traditional measurement methods and MS monitoring, traditional monitoring data were collected from multipoint extensometers installed at Stake 116.30 m at the upstream sidewall in the main powerhouse. Fig.21 shows the location of multipoint extensometer

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M4CF5-2 and its absolute displacement processes graph. The C4, C5 and C6 benches of the main powerhouse resulted in jumps in the displacement line, especially from the beginning of April to the end of September 2013 (highlighted with a light yellow shadow). More than 50 mm of displacement deformation occurred at the upstream sidewall of the main powerhouse at the Stake 0+116.30 m (along the Y axis). Coincidentally, the recorded MS events were concentrated near the upstream sidewalls of the main powerhouse at an elevation of 1721.20 m at the Stake 116.30 m during this period, as shown in Fig.20. An analysis of the supervised multipoint extensometer data showed that the deformation of the upstream sidewall at the main powerhouse was closely related to the MS events frequency and magnitude. However, the former results lagged behind seismic monitoring results. The aggregation of the MS events at the upstream sidewall of the main powerhouse typically appeared at least one week 15

ACCEPTED MANUSCRIPT before apparent changes were recorded in the multipoint extensometer, M4CF5-2. Thus, the initiation, propagation and coalescence of the MS events can be regarded as precursors to the

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surface deformation and the eventual instability failure of the surrounding rock mass.

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4. Modeling and assessment of underground cavern stability

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4.1 Brief outline of the RFPA2D code

The RFPA2D, a FEM based code, can be used to simulate the macroscopic behavior that ranges from brittle to ductile and is associated with localized or diffused rock damage. In

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addition, this model describes the temporal and spatial evolution of AE or MS, including the size (energy released) and location of rupture during the progressive damage process. The

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maximum tensile strain criterion and the modified Mohr-Coulomb criterion with a tension cutoff were used as two damage thresholds in the damage mechanics-based model (Jeager et

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al., 2007). Additional details regarding the application and description of the RFPA code can

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be found in Tang et al. (1998) and in other literatures (Dai et al., 2014; Xu et al., 2012b,

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2014b; Wang et al., 2013; Wei et al., 2014; Li et al., 2006).

To reflect the material heterogeneity at a meso-level, the mechanical parameters including the strength and Young’s modulus of the mesoscopic material elements are

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randomly assigned from Weibull statistic distribution as follows:

m u  f u     u0  u0 

m1

 u exp    u0 

m

(1)

where u is the macroscopic magnitude of the parameters (such as the Young’s modulus, Poisson’s ratio, strength properties) and represents the real values obtained from laboratory tests. In addition, the scale parameter u0 is related to the average of the element parameters corresponding to u and is used as an input values in the numerical simulation (Li et al., 2014b; Tang et al., 2000). The parameter m defines the shape of the distribution function. In the RFPA code, m is defined as the homogeneity index of the material. When referring to the Weibull distribution and the definition of the homogeneity index, a larger value of m implies a more homogeneous material and vice versa. Heterogeneous material can be produced

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ACCEPTED MANUSCRIPT numerically in a computer simulation for a material composed of many elements. Each element is assumed to be isotropic and homogeneous. Systematic studies of the homogeneity

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index m have been published previously (Tang et al., 2000; Wong et al., 2006).

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4.2 Model setup

A typical transverse section of the underground group caverns (see Fig.5) was selected to simulate the failure processes subjected to excavation. Fig.22 shows the numerical modeling

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produced from Fig.4 for the excavation sequence and Fig.5 for the geological structures. The boundaries were placed sufficiently far from the upstream sidewall of the main powerhouse

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and the downstream sidewall of the tailrace surge chamber to minimize their effects on the modeling results. The model is discretised into a mesh that contains 192,000 elements with a size of 480 m×400 m. A roller boundary condition (i.e. zero normal velocity/displacement)

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was used for the bottom boundary, and the stress constraints after back calculation from

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in-situ stress were applied to the horizontal and top boundaries. To clearly show the effect of excavation activities on surrounding rock mass of the underground caverns, the evolutionary

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process of surrounding rock mass behavior in this model is simulated by step-by-step excavation. Six benches of the main powerhouse and tailrace surge chamber were initially

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considered in this model. For each step the excavation is advanced according to the construction schedule, as shown in Fig.4. The model is solved in a quasi-static fashion to reach a stress equilibrium state. The mechanical parameters employed in the modelling can be obtained in related reference (Cheng et al., 2014). For simplicity, only the main rock masses and faults were considered in this study.

4.3 Numerical modeling results and comparison with microseismicity and visual deformation Fig.23 compares the potential failure surfaces between the numerical simulation using the RFPA code and the MS concentration captured by the MS monitoring system. The numerical simulation results were correlated well with the MS swarms inside the middle sidewall between the main powerhouse and transformer chamber, especially along the faults such as g1-4-14 and g1-4-15. The microcracking band dip obtained from the numerical 17

ACCEPTED MANUSCRIPT simulations and the MS concentration was 21°, as shown in Fig.23b, c. This band dip was similar to the fault dips of g1-4-14 and g1-4-15 (14°, as shown in Fig.5). As the excavation progressed, microcrackings were observed that began in the footwall regions of the g1-4-14

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and g1-4-15 faults and grew to the hanging wall, as shown in Fig.24 (steps 3, 4 and 5). A

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critical failure surface has been formed when the step 4 excavation was reached. The AE

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distribution of each step excavation in the underground caverns is shown in Fig.24. To compare the numerical simulation results in detail, Fig.23c shows the spatial distribution of seismic activity that occurred near faults g1-4-14 and g1-4-15 between November 1, 2013 and

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January 14, 2014, as illustrated in Fig.17. The strike of the MS activity zones matched the AE distribution along the g1-4-14 and g1-4-15 faults. Meanwhile, the damage zones identified by

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the location of the predominant MS activity (Fig.23c) corresponded with the modeled high-stress zones (Fig.23a), which indicated that MS monitoring can be effectively used to

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determine cracks initiation and growth in deep rock masses. Furthermore, the measured data

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of multipoint extensometers (M4CF3-8 in the downstream sidewall of main powerhouse, M4CF3-10 in the upstream sidewall of transformer chamber, as shown in Figs.25 and 26) near

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the g1-4-14 and g1-4-15 faults demonstrated that the visual deformation of the downstream sidewall of the main powerhouse and the upstream sidewall of transformer chamber was convergent although excavation progresses after August, 2013. Therefore, a comprehensive

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analysis incorporating numerical simulation, MS monitoring, multipoint extensometer results and geological structures can be used as a preliminary evaluation of the stability of underground caverns.

Some slottings were conducted in the main powerhouse at the end of 2013 to analyze the deformation mechanism of surrounding rock masses thoroughly at the downstream sidewall of the main powerhouse and the MS concentrations occurred near the 2# and 3# omnibus bar caves (Fig.17). The damage mechanism in slotting and the corresponding geological sketch map are shown in Fig.27, which was taken at the downstream sidewall of the main powerhouse along the center line of the 2# omnibus bar cave (Stake 0+51.3 m). Compared with the previous excavation surface without a concrete lining, the characteristics of the intact rock mass in the slotting zone significantly changed. For example, the fractured rock mass 18

ACCEPTED MANUSCRIPT existed in the slotting zone with N5°W/NE∠550 and a length of 1.1 m. Moreover, short cracks developed in the slotting area that were of 10-20 cm long (Fig.27b). These cracks demonstrated that the damage mechanisms of the critical failure surface of the underground

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group cavern coincided with what were observed in-situ, via either numerical method or MS

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monitoring approach. In particular, shear fractures were observed at the footwall of the middle

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sidewall (Fig.23b), which corresponded with the common damage phenomena of the surrounding rock mass on site (Fig.19). The development of failures in the surrounding rock mass facilitates our understanding of where the damage zones initiated, how they initiated and

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how they propagated. Furthermore, these results indicate where rock bridges broke during the

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development of the failure surfaces and how each of the destabilized blocks of rock moved.

Consequently, excavation-induced MS activity can be regarded as a precursor of the

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deformation of the surrounding rock mass and even instability failure of the underground

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group caverns. The evolutionary pattern of stress accumulation, stress release and stress migration in the preparation processes of the potential instability risk in rock engineering is

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consistent with the spatial distribution of MS events (Xu et al., 2012a). When integrated with traditional monitoring, in-situ observation and the correlations between them, these two tools (i.e. MS monitoring and numerical simulation) are useful for explaining the behavior of the

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potential instability mechanisms of underground structures. Thus, the internal effects and correlations between the MS activity and stress field in the deep rock mass of underground group caverns subjected to excavation-induced unloading can be analyzed in detail.

5. Conclusions The MS monitoring technique was successfully applied to underground group caverns at the Houziyan hydropower station to simultaneously monitor, analyze and evaluate the stability of the surrounding rock mass during excavation. The tempo-spatial distribution of the recorded MS events indicated that the failure zones revealed by intense MS activities primarily corresponded with the leading edge of the excavation faces and pre-existing joints,

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ACCEPTED MANUSCRIPT faults and some geological structures (Figs. 12, 14, 17 and 20). This finding demonstrated the ability to identify the regions in the underground group caverns where the MS activities were active or inactive. A detailed analysis of the MS data from excavating the underground group

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caverns demonstrated the enormous potential of tracking excavation progress and a better

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understanding of the excavation process and seismic hazards in underground engineering.

In addition, the underground structures were numerically modeled considering the rock heterogeneity. The fracturing processes of rocks subjected to unloading were simulated to

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investigate the failure mode described above and to determine the stability of the underground group caverns, which suggests that the observed deformation and damage behavior directly

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resulted from the strike-slip of pre-existing faults (i.e., g1-4-14 and g1-4-15), the growth of these fractures and the possible formation of new fractures, which opened up due to the

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further extension straining of the surrounding rock mass. The present results demonstrate that

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the MS monitoring technique can be employed as a 3D real-time “body” monitoring method to evaluate the stability of surrounding rock masses and the potential damage mechanisms in

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deep-buried underground engineering, especially when subjected to excavation-induced unloading. A comprehensive approach that integrates MS monitoring, numerical simulation, traditional surveying and in-situ observation results in a more comprehensive understanding

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of the excavation behaviors of the surrounding rock mass in underground group caverns and presents more satisfactory controls for engineering safety.

Acknowledgements The authors are grateful for the financial support from the National Program on Key basic Research Project (No. 2015CB057903), National Natural Science Foundation of China (No. 51209127, 51374149), Program for New Century Excellent Talents in University (NCET-13-0382), Youth Science and Technology Fund of Sichuan Province (2014JQ0004) and the Opening fund of State Key Laboratory of Geohazard Prevention and Geoenvironment Protection (Chengdu University of Technology) (No. SKLGP2013K013).

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ACCEPTED MANUSCRIPT Captions:

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Fig.1 Regional map of the Houziyan hydropower station

Fig.3

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Fig.2 3D layout of the underground group caverns of Houziyan hydropower station

A typical geological cross-section of the left and right bank slope of Houziyan

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hydropower station nearby the dam axis (40 m downstream of the dam axis)

The specific stratified excavation scheme of the underground group caverns

Fig.5

A typical geological cross-section of Houziyan hydropower station powerhouse along

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Fig.4

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the center line of 2# omnibus bar cave (Stake 0+51.3 m)

A stereographic projection of the faults in Fig.5

Fig.7

Distribution diagram of in-situ stress measurement points at the underground group

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Fig.6

Fig.8

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cavern of Houziyan hydropower station

(a) The disklike rock cores from in-situ stress drilling, and (b) rib spalling at the

horizontal depth of 385 m in SPD1-5

Fig.9 Sketch map of accelerometer array at the underground group caverns of Houziyan hydropower station. The grey cylinders represent accelerometers. The sensor array includes 18 channels with a triaxial accelerometer S8.

Fig.10

Typical waveforms for a standard MS event recorded in November 26, 2013 at the

underground caverns

Fig.11 Temporal distribution of seismic events during the selected period between April 12 26

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Fig.12

The spatial distribution of MS events at the underground caverns during the selected

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period between April 12 and July 11, 2013. (a) spatial distribution of MS events, (b) density

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phenomena induced by excavation unloading at zones I, II, III

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contour of MS events corresponding to (a), and (c) the corresponding photos of damage

Fig.13 Spatial distribution of MS events with moment magnitude greater than 0 recorded

(a) Cross-section view of the east-north projection of the MS events recorded

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Fig.14

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between April 12 and July 11, 2013

between May 16 and May 21, 2013, and (b) aerial view of the monitoring area is shown to

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illustrate the correlation between seismic source locations and underground structures (the

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spheres present MS events, the color presents moment magnitude. The lighter the sphere is,

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the higher the moment magnitude is, and vice versa.)

Fig.15 Seismic source density contour in (a) south-east vertical cross-section looking north, and (b) north-easting plane looking down. Different colors represent various quantities of

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seismic source locations per unit area

Fig.16 Shotcrete fractures and spalling occurred at the sidewall of the 2# omnibus bar cave

Fig.17

(a) Cross-section view of the east-north projection of the MS events recorded

between November 1, 2013 and January 14, 2014, and (b) aerial view of the monitoring area is shown to illustrate the relationship between seismic source locations and underground structures

Fig.18 Corresponding density contour of seismic events recorded between November 1, 2013 and January 14, 2014. (a) south-east vertical cross-section looking north, and (b) north-easting plane looking down 27

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Fig.19 Shotcrete cracks and spalling nearby the footwall of faults g1-4-14 and g1-4-15

Fig.21

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during the selected period between May 24 and June 1, 2013.

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Fig.20 Spatial distribution and its corresponding density contour of MS events recorded

Absolute displacement processes graph of multipoint extensometer M4CF5-2 at

elevation 1721.2 m, Stake 0+116.3 m (along Y axis) of the upstream sidewall in main

Numerical model of underground group caverns in terms of elastic modulus

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Fig.22

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powerhouse

Numerical simulation results show strong correlation with some achievement of MS

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Fig.23

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(excavation sequence by the end of 2013)

data inside the middle sidewall between the main powerhouse and transformer chamber: (a)

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maximum principal stress distribution; (b) AE distribution; (c) MS swarms. (The lighter the areas are, the higher the stress is in (a). The red circles in the AE figure express tensile fractures, while the white ones express compressive fractures and the black ones represent the

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final failure mode. Meanwhile, the size of the circle means the released energy of AE. The bigger the circle is, the more the released energy of AE in (b).)

Fig.24

The evolution of AE distribution of each step excavation in the underground caverns

Fig.25

Absolute displacement processes graph of multipoint extensometer M4CF3-8 at

elevation 1706.5 m, Stake 0+051.3 m (along Y axis) of the downstream sidewall in the main powerhouse

Fig.26

Absolute displacement processes graph of multipoint extensometer M4CF3-10 at

elevation 1721.2 m, Stake 0+051.3 m (along Y axis) of the upstream sidewall in the transformer chamber 28

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Fig.27

(a) The photograph of failure mode taken in slotting at Stake 0+51.3 m of

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downstream sidewall and (b) its corresponding geologic sketch map

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Figure 27

56

ACCEPTED MANUSCRIPT Highlights Microseismic monitoring technique is adopted to assess underground caverns stability.



Tempo-spatial distribution and characteristics of microseismicity are analyzed.

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Correlation of microseismicity with pre-existing geological structures is evidenced.

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The results of microseismic monitoring and numerical simulation are similar.

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57