1
2. THE STUDY CASE On March 2007 a shallow translational landslide (with a volume of about 10 4 m 3 ) affected the slope of a major road, thus completely destroying the al- ready constructed structures. Geological and geo- morphological evidences of an old deep rototrans- lational slide of a total volume of about 10 6 m 3 in- volving jointed gneiss and the overlying Pliocene and Pleistocene sands were recognized. A tunnel excavation re-started in November 2009 with three main excavation phases definitively stopped in February 2010, after the realization of 28 m of tun- nel (Fig. 1) due to safety reasons. The long term continuous monitoring of the entire slope af- fected by some land- slides by means of a ground based interfer- ometric apparatus (GBInSAR) (Bozzano et al. 2011) allowed to identify typical defor- mational creep on both natural slope and man made structures (Figs 2-3): 1. man-made slope af- fected by small exca- vation; a) covered by spritz -beton; b) not-covered by spritz-beton; 2. anchored bulk- heads. 1. INTRODUCTION Threshold model to identify time of failure of a slope affected by displacements, based on the Voight model (Voight 1988): (1) where =displacement, =velocity, t=time, suffix f refer to time of failure, A and =constants. For >1 and 2; this equation contains four different pa- rameters A, , t f (time of failure) and f (velocity at t f ) (Crosta & Agliardi 2003). ASSESSING OF FAILURE PREDICTION METHODS FOR SLOPE AFFECTED BY HUMAN ACTIVITIES 3.2 Anchored bulkheads Since they did not reach the collapse, in addition to and A, also f or f must be inferred. A step by step new method was implemented (see the text of the paper for more details) and the pre-failure velocity time series were reconstructed as follows: (3) (4) where t 0 , 0 are the initial time and veloc- ity, respectively (Tab. 2, Fig. 4). In Tab. 2 and Fig. 4 the first order of bulkhead has been analyzed by looking at the di- splacement related to the three tunnel excavation phases. At present, the per- formance of the com- puted pre-failure velocity time series cannot be tested in term of f or f , but the fitting with the recorded part of the allowable ti- me series is satisfying. 4.CONCLUSIONS In Fig. 5, A and values referred to all the data-set are reported and grouped for each catego- ry: a clear distinction can be inferred: values lower than those reported in literature for natu- ral slopes have been achieved for landslides interacting with structures (spritz-beton and an- chored bulkheads). Also the A parameter showed typical values one order of magnitude higher than those conventionally observed for landslides in natural slopes. A peculiar behaviour has been identified by analyzing the deformation of anchored bulkheads. By looking at the deformations in- duced by three successive excavation phases we identified a trend toward the reduction of A value and the in- crease of values. This is consistent with the expected stiffness decrease of the slope/bulkhead system due to the increase of the total amount of dis- placement (i.e. going from the first to the third excavation phase). Hence, typical and A values for landslide structure interaction have been achieved, thus allowing for a wider ap- plication of Crosta & Agliardi method (Crosta & Agliardi 2003). ) 1 ( ) 2 ( ) 1 ( f f ) 1 ( ) 2 ( 1 f ) t t )( 1 ( A t ) 1 ( A ) 2 ( A 1 Tab. 2 Parameters of the first order of anchored bulkhead Fig. 4 Monitored time series of displacement and corresponding curves of Eqs 1-2 in the left axis, and curves of velocity of Eqs 3-4 in the right axis Fig. 1 Picture of the slope showing the monitoring sensor Fig. 5 Ellipses identify groups characterized by similar va- lues of A and ; the black arrows show the trend of and A REFERENCES Bozzano, F., Cipriani, I., Mazzanti, P. and Prestininzi, A. 2011. Displacement patterns of a landslide affected by human activi- ties: insights from ground-based InSAR monitoring. Natural Hazards, 59-3:1377-1396. DOI 10.007/s11069-011-9840-6. Crosta, G.B. & Agliardi F. 2003. Failure forecast for large rock slides by surface displacement measurements. Can. Geotech. J. 40: 176-91. Fukuzono, T. 1985. A new method for predicting the failure time of a slope, Tokyo, Japan Landslide Society. Proceedings of the fourth international conference and field workshop on landslides 145–50. Voight, B. 1988. A relation to describe rate-dependent material failure. Science 243: 200-203. 1 : ) t t )( 1 ( A 1 1 1 0 0 3. FAILURE PREDICTION 3.1 Man-made slopes The most effective values of A, and f of Eq. 1 have been derived for each occurred landslide (Figs 1-3) in some cases involving a part of slope covered by spritz-beton, in some others with- out this coverage. In order to avoid the limitation derived from values close to 1 and in the range between 0 and 1, the following formula was implemented by a double integration in time of the original Fukuzono one (Fukuzono 1985); (2) where f is the cumulative dis- placement before failure. Then, best fitting analyses of the en- tire dataset were performed by using both Eq. 1 and Eq. 2, thus obtaining two A and pa- rameters for each landslide. In Tab. 1 the corresponding values referred to four selected and representative landslide case histories are reported: the good performance in that way ob- tained can be appreciated by the very limited difference be- tween recorded and computed time of failure, velocity an dis- placement. The entire allowable data-set is in the paper. Fig. 3 Time series of displacement and the best fitting by Eqs 1-2 of the four selected landslides of Tab. 1 Francesca Bozzano (1,2,3) , Ivan Cipriani (2) , Paolo Mazzanti (1,2,3) (1) CERI Research Centre, “Sapienza” Università di Roma, Rome, Italy [email protected] (2) Department of Earth Sciences, “Sapienza” Università di Roma, Rome, Italy [email protected] (3) NHAZCA S.r.l., spin-off “Sapienza” Università di Roma, Via Cori snc, 00177, Rome, Italy [email protected] Tab. 1 Parameters of four selected landslides. Bold numbers cor- respond to the best fitting (Figs 2-4) ) 1 ( ) 2 ( ) 1 ( ) 2 ( f f t ) 1 ( A t ) 1 ( A ) 2 ( A 1 1 : ) t t )( 1 ( A 1 1 1 f f Fig. 2 Displacement time series (obtained by interferometric and topo- graphic monitoring) of the three anchored bulkheads

Assessing of failure prediction methods for slope affected by human activities

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BOZZANO FRANCESCA, CIPRIANI IVAN, MAZZANTI PAOLO

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Page 1: Assessing of failure prediction methods for slope affected by human activities

2. THE STUDY CASE On March 2007 a shallow translational landslide (with a volume of about 104 m3) affected the slope of a major road, thus completely destroying the al-ready constructed structures. Geological and geo-morphological evidences of an old deep rototrans-lational slide of a total volume of about 106 m3 in-volving jointed gneiss and the overlying Pliocene and Pleistocene sands were recognized. A tunnel excavation re-started in November 2009 with three main excavation phases definitively stopped in February 2010, after the realization of 28 m of tun-nel (Fig. 1) due to safety reasons. The long term continuous monitoring of the entire slope af-fected by some land-slides by means of a ground based interfer-ometric apparatus (GBInSAR) (Bozzano et al. 2011) allowed to identify typical defor-mational creep on both natural slope and man made structures (Figs 2-3): 1. man-made slope af-fected by small exca-vation; a) covered by spritz

-beton; b) not-covered by

spritz-beton; 2. anchored bulk-heads.

1. INTRODUCTION Threshold model to identify time of failure of a slope affected by displacements, based on the Voight model (Voight 1988):

(1)

where Ω=displacement, Ω=velocity, t=time, suffix f refer to time of failure, A and =constants. For >1 and ≠2; this equation contains four different pa-rameters A, , tf (time of failure) and Ωf (velocity at tf) (Crosta & Agliardi 2003).

ASSESSING OF FAILURE PREDICTION METHODS

FOR SLOPE AFFECTED BY HUMAN ACTIVITIES

3.2 Anchored bulkheads Since they did not reach the collapse, in addition to and A, also Ωf or Ωf must be inferred. A step by step new method was implemented (see the text of the paper for more details) and the pre-failure velocity time series were reconstructed as follows:

(3) (4)

where t0, Ω0 are the initial time and veloc-ity, respectively (Tab. 2, Fig. 4). In Tab. 2 and Fig. 4 the first order of bulkhead has been analyzed by looking at the di-splacement related to the three tunnel excavation phases. At present, the per-formance of the com-puted pre-failure velocity time series cannot be tested in term of Ωf or Ωf, but the fitting with the recorded part of the allowable ti-me series is satisfying.

4.CONCLUSIONS

In Fig. 5, A and values referred to all the data-set are reported and grouped for each catego-ry: a clear distinction can be inferred: values lower than those reported in literature for natu-ral slopes have been achieved for landslides interacting with structures (spritz-beton and an-chored bulkheads). Also the A parameter showed typical values one order of magnitude higher than those conventionally observed for landslides in natural slopes. A peculiar behaviour has been identified by analyzing the deformation of anchored bulkheads. By looking at the deformations in-duced by three successive excavation phases we identified a trend toward the reduction of A value and the in-crease of values. This is consistent with the expected stiffness decrease of the slope/bulkhead system due to the increase of the total amount of dis-placement (i.e. going from the first to the third excavation phase). Hence, typical and A values for landslide structure interaction have been achieved, thus allowing for a wider ap-plication of Crosta & Agliardi method (Crosta & Agliardi 2003).

)1(

)2()1(

ff)1(

)2(1

f )tt)(1(At)1(A)2(A

1

Tab. 2 Parameters of the first order of anchored bulkhead

Fig. 4 Monitored time series of displacement and corresponding curves of Eqs 1-2 in the left axis, and curves of velocity of Eqs 3-4 in the right axis

Fig. 1 Picture of the slope showing the monitoring sensor

Fig. 5 Ellipses identify groups characterized by similar va-

lues of A and ; the black arrows show the trend of and A

REFERENCES

Bozzano, F., Cipriani, I., Mazzanti, P. and Prestininzi, A. 2011. Displacement patterns of a landslide affected by human activi-ties: insights from ground-based InSAR monitoring. Natural Hazards, 59-3:1377-1396. DOI 10.007/s11069-011-9840-6.

Crosta, G.B. & Agliardi F. 2003. Failure forecast for large rock slides by surface displacement measurements. Can. Geotech. J. 40: 176-91.

Fukuzono, T. 1985. A new method for predicting the failure time of a slope, Tokyo, Japan Landslide Society. Proceedings of the fourth international conference and field workshop on landslides 145–50.

Voight, B. 1988. A relation to describe rate-dependent material failure. Science 243: 200-203.

1:)tt)(1(A 11

100

3. FAILURE PREDICTION

3.1 Man-made slopes The most effective values of A, and Ωf of Eq. 1 have been derived for each occurred landslide (Figs 1-3) in some cases involving a part of slope covered by spritz-beton, in some others with-out this coverage. In order to avoid the limitation derived from values close to 1 and in the range between 0 and 1, the following formula was implemented by a double integration in time of the original Fukuzono one (Fukuzono 1985);

(2)

where Ωf is the cumulative dis-placement before failure. Then, best fitting analyses of the en-tire dataset were performed by using both Eq. 1 and Eq. 2, thus obtaining two A and pa-rameters for each landslide. In Tab. 1 the corresponding values referred to four selected and representative landslide case histories are reported: the good performance in that way ob-tained can be appreciated by the very limited difference be-tween recorded and computed time of failure, velocity an dis-placement. The entire allowable data-set is in the paper.

Fig. 3 Time series of displacement and the best fitting by Eqs 1-2 of the four selected landslides of Tab. 1

Francesca Bozzano(1,2,3), Ivan Cipriani(2), Paolo Mazzanti(1,2,3)

(1) CERI Research Centre, “Sapienza” Università di Roma, Rome, Italy [email protected]

(2) Department of Earth Sciences, “Sapienza” Università di Roma, Rome, Italy [email protected]

(3) NHAZCA S.r.l., spin-off “Sapienza” Università di Roma, Via Cori snc, 00177, Rome, Italy [email protected]

Tab. 1 Parameters of four selected landslides. Bold numbers cor-respond to the best fitting (Figs 2-4)

)1(

)2(

)1(

)2(

ff t)1(At)1(A)2(A

1

1:)tt)(1(A 11

1ff

Fig. 2 Displacement time series (obtained by interferometric and topo-graphic monitoring) of the three anchored bulkheads