# Geotechnical Analysis and 3D Fem Modeling of Ville San Pietro (Italy)

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## Abstract

**:**

## 1. Introduction

- The hydrological–geotechnical analysis;
- The study of the hydro-mechanical contribution from the vegetation and, eventually, for a landslide risk mitigation by using soil bio-engineering countermeasures. In fact, the relevance of the contribution of plant roots to prevent the instability and the soil erosion has been long observed and it is recognized [6,7,8,9];
- The hydro-geological risk management. In fact, it is well known that landslide risk conditions persist for long after the officially issued alert has been ceased. For instance, by monitoring the soil water content, it would be possible to understand when people, subject to removal, can return to their homes safely.

- Preliminary study of the site;
- Identification of the places where the nodes of the LAMP network should be positioned;
- Comparison with IHG analyses based on monitoring measures.

## 2. Materials and Methods

#### 2.1. Ville San Pietro: Location, Description of the Landslide, Investigations and Monitoring

#### 2.1.1. Site and Landslide Description

^{6}m), suffering reactivations over time (Figure 2). Typical phenomena are falls (where there are rock outcrops), slides and flows (in the shallow blanket that characterizes the area).

#### 2.1.2. Geotechnical Surveys

#### 2.1.3. Geophysical Surveys

_{P}and V

_{S}, respectively). The geophysical investigations confirmed the presence of two layers: the blanket (the shallow layer characterized by a low primary wave velocity V

_{P}= 378 m/s) and the bedrock (the deep rock layer characterized by high primary wave velocity V

_{P}= 832 m/s).

#### 2.1.4. Monitoring by Inclinometers and Piezometers

#### 2.1.5. SAR Interferometry Monitoring

#### 2.2. Three-Dimensional Finite Element Modeling of Ville San Pietro

#### 2.2.1. Governing Equations

#### 2.2.2. Slope Model Geometry and Discretization

#### 2.2.3. Church Modeling

#### 2.2.4. Slope Model Parameters

_{dry}, γ

_{sat}, respectively), pertinent to each layer; these values are also confirmed by the geophysical test results.

_{dry}and γ

_{sat}values reported in Table 3, while c′ was assumed equal to 0 kPa and φ′ equal to 22°, which are the most punitive values from the test result elaborations. These analyses were conducted on three significant cross-sections of the slope with several water table levels and in all these cases the provided Safety Factors were less than one (about 0.5–0.7). These results were not coherent with the observed slope behavior. Therefore, additional preliminary finite element analyses (on the aforementioned slope cross-sections) were carried out increasing the above strength parameters, but always referring to the experimental test results. The adopted values of γ

_{dry}, γ

_{sat}, v and E are indicated in Table 3 (the estimate of the stiffness parameters is described below). In particular, characterizing the blanket with the values of cohesion and friction angle from the direct shear test, the analyses disagreed to the actual slope response.

_{S}) values and then, by the Equation (1) the value of the initial shear stiffness G

_{0}

_{S}= 150 m/s and 444 m/s is, respectively, used. Table 3 indicates the set of parameters adopted for the numerical simulations (K

_{0}is the coefficient of lateral earth pressure). The Mohr–Coulomb constitutive model is adopted for the blanket and the bedrock. The shear stiffness G is assumed equal to the initial value G

_{0}.

- ${E}_{50}^{ref}$ reference stiffness modulus for primary loading, corresponding to the reference pressure
- ${E}_{ur}^{ref}$ reference Young’s modulus for unloading and reloading, corresponding to the reference pressure
- ${E}_{oed}^{ref}$ oedometer modulus, corresponding to the reference pressure
- m power for stress-level dependency of stiffness

## 3. Results

#### 3.1. Results of the Numerical Analysis Simulating the Groundwater Rise Occurred in January 2018–March 2018

#### 3.2. Results of the Numerical Analysis Simulating the Groundwater Fall Occurred in March 2018–June 2018

#### 3.3. Numerical Analysis Results, On-Site Inspection and SAR Interferometry Data

## 4. Discussion

^{6}m

^{3}. It is composed of a debris blanket and a stable bedrock and to better represent the real slope, the church load is introduced, albeit in a simplified way. For the usual purposes of geotechnical engineering analyses, this is quite uncommon, because the introduction of loads and the modelling of structures in 3D numerical models are onerous operations with regard to the determination of the geometry and material parameters, and the time consumption for calculation and output interpretation.

## 5. Conclusions

## Author Contributions

## Funding

## Acknowledgments

## Conflicts of Interest

## References

- Bovolenta, R.; Passalacqua, R.; Federici, B.; Sguerso, D. LAMP-Landslide Monitoring and Predicting for the Analysis of Landslide Susceptibility Triggered by Rainfall Events. In Landslides and Engineered Slopes Experience, Theory and Practice, Proceedings of the 12th International Symposium on Landslides, Napoli, Italy, 12–19 June 2016; CRC Press: Boca Raton, FL, USA, 2016; Volume 2, pp. 517–522. [Google Scholar]
- Passalacqua, R.; Bovolenta, R.; Federici, B. An Integrated Hydrological-Geotechnical Model in GIS for the Analysis and Prediction of Large-Scale Landslides Triggered by Rainfall Events. In Engineering Geology for Society and Territory; Springer International Publishing: Cham, Switzerland, 2015; Volume 2, pp. 1799–1803. [Google Scholar] [CrossRef]
- Passalacqua, R.; Bovolenta, R.; Federici, B.; Balestrero, D. A Physical Model to Assess Landslide Susceptibility on Large Areas: Recent Developments and Next Improvements. Procedia Eng.
**2016**, 158, 487–492. [Google Scholar] [CrossRef][Green Version] - Campora, M.; Palla, A.; Gnecco, I.; Bovolenta, R.; Passalacqua, R. The laboratory calibration of a soil moisture capacitance probe in sandy soils. Soil Water Res.
**2020**, 15, 75–84. [Google Scholar] [CrossRef][Green Version] - Bovolenta, R.; Iacopino, A.; Passalacqua, R.; Federici, B. Field Measurements of Soil Water Content at Shallow Depths for Landslide Monitoring. Geosciences
**2020**, 10, 409. [Google Scholar] [CrossRef] - Bovolenta, R.; Mazzuoli, M.; Berardi, R. Soil bio-engineering techniques to protect slopes and prevent shallow landslides. Riv. Ital. Geotec.
**2018**, 52, 44–65. [Google Scholar] - Mazzuoli, M.; Bovolenta, R.; Berardi, R. Experimental Investigation on the Mechanical Contribution of Roots to the Shear Strength of a Sandy Soil. Procedia Eng.
**2016**, 158, 45–50. [Google Scholar] [CrossRef][Green Version] - Pagano, L.; Reder, A.; Rianna, G. Effects of vegetation on hydrological response of silty volcanic covers. Can. Geotech. J.
**2019**, 56, 1261–1277. [Google Scholar] [CrossRef] - Tagarelli, V.; Cotecchia, F. The Effects of Slope Initialization on the Numerical Model Predictions of the Slope-Vegetation-Atmosphere Interaction. Geosciences
**2020**, 10, 85. [Google Scholar] [CrossRef][Green Version] - Bovolenta, R.; Federici, B.; Berardi, R.; Passalacqua, R.; Marzocchi, R.; Sguerso, D. Geomatics in support of geotechnics in landslide forecasting, analysis and slope stabilization. Geoing. Ambient. Min.
**2017**, 151, 57–62. [Google Scholar] - Nakai, T.; Xu, L.; Yamazaki, H. 3D and 2D Model Tests and Numerical Analyses of Settlements and Earth Pressures Due to Tunnel Excavation. Soils Found.
**1997**, 37, 31–42. [Google Scholar] [CrossRef][Green Version] - Ye, G.; Zhang, F.; Yashima, A.; Sumi, T.; Ikemura, T. NUMERICAL ANALYSES ON PROGRESSIVE FAILURE OF SLOPE DUE TO HEAVY RAIN WITH 2D AND 3D FEM. Soils Found.
**2005**, 45, 1–15. [Google Scholar] [CrossRef][Green Version] - Do, N.A.; Dias, D. A comparison of 2D and 3D numerical simulations of tunnelling in soft soils. Environ. Earth Sci.
**2017**, 76, 1–12. [Google Scholar] [CrossRef] - Duncan, J.M. Soil slope stability analysis. In Landslides: Investigation and Mitigation; Transportation Research Board: Washington, DC, USA, 1996; Volume 247, pp. 337–371. [Google Scholar]
- Griffiths, D.V.; Marquez, R.M. Three-dimensional slope stability analysis by elasto-plastic finite elements. Géotechnique
**2007**, 57, 537–546. [Google Scholar] [CrossRef][Green Version] - Griffiths, D.V.; Huang, J.; Fenton, G.A. On the reliability of earth slopes in three dimensions. Proc. R. Soc. A Math. Phys. Eng. Sci.
**2009**, 465, 3145–3164. [Google Scholar] [CrossRef][Green Version] - Liu, Y.; Zhang, W.; Zhang, L.; Zhu, Z.; Hu, J.; Wei, H. Probabilistic stability analyses of undrained slopes by 3D random fields and finite element methods. Geosci. Front.
**2018**, 9, 1657–1664. [Google Scholar] [CrossRef] - Saeed, M.S.; Maarefvand, P.; Yaaghubi, E. Two and three-dimensional slope stability analyses of final wall for Miduk mine. Int. J. Geo-Eng.
**2015**, 6, 1105. [Google Scholar] [CrossRef][Green Version] - Ersoy, H.; Kaya, A.; Angın, Z.; Dağ, S. 2D and 3D numerical simulations of a reinforced landslide: A case study in NE Turkey. J. Earth Syst. Sci.
**2020**, 129, 1–12. [Google Scholar] [CrossRef] - Bossi, G.; Borgatti, L.; Gottardi, G.; Marcato, G. Quantification of the uncertainty in the modelling of unstable slopes displaying marked soil heterogeneity. Landslides
**2019**, 16, 2409–2420. [Google Scholar] [CrossRef] - Capitani, M.; Chelli, A.; Del Seppia, N.; Federici, P.R.; Serani, A. Atlante dei Centri Abitati Instabili della Liguria-IV. Provincia di Imperia; Regione Liguria: Genova, Italy, 2007; pp. 138–141. [Google Scholar]
- Passalacqua, R.; Bovolenta, R.; Spallarossa, D.; De Ferrari, R. Geophysical site characterization for a large landslide 3-D modelling. In Geotechnical and Geophysical Site Characterization 4, Proceedings of the 4th International Conference on Site Characterization 4; Taylor and Francis Group: London, UK, 2013; Volume 2, pp. 1765–1771. [Google Scholar]
- Nakamura, Y. Method for dynamic characteristics estimation of subsurface using microtremor on the ground surface. In Quarterly Report of RTRI; Railway Technical Research Institute: Tokyo, Japan, 1989; Volume 30, pp. 25–33. [Google Scholar]
- Noviello, C.; Verde, S.; Zamparelli, V.; Fornaro, G.; Pauciullo, A.; Reale, D.; Nicodemo, G.; Ferlisi, S.; Gulla, G.; Peduto, D. Monitoring Buildings at Landslide Risk With SAR: A Methodology Based on the Use of Multipass Interferometric Data. IEEE Geosci. Remote. Sens. Mag.
**2020**, 8, 91–119. [Google Scholar] [CrossRef] - Meisina, C.; Notti, D.; Zucca, F.; Ceriani, M.; Colombo, A.; Poggi, F.; Roccati, A.; Zaccone, A. The use of PSinSAR™ and SqueeSAR™ techniques for updating landslide inventories. In Landslide Science and Practice: Landslide Inventory and Susceptibility and Hazard Zoning; Springer: Berlin, Germany, 2013; Volume 1, pp. 81–87. [Google Scholar]
- Duncan, J.M. State of the Art: Limit Equilibrium and Finite-Element Analysis of Slopes. J. Geotech. Eng.
**1996**, 122, 577–596. [Google Scholar] [CrossRef] - Brinkgreve, R.B.J.; Bakker, H.L. Non-linear finite element analysis of safety factors. In Proceedings of the 7th International Conference on Computer Methods and Advances in Geomechanics, Cairns, Australia, 6–10 May 1991; pp. 1117–1122. [Google Scholar]
- Roccaforte, F.; Cucinotta, C. Stima dei Parametri Geotecnici in Geofisica Applicata, 1st ed.; Dario Flaccovio Editore: Palermo, Italy, 2015. [Google Scholar]
- Schanz, T.; Vermeer, P.; Bonnier, P. The hardening soil model: Formulation and verification. In Proceedings of the Beyond 2000 in Computational Geotechnics; Informa UK Limited: London, UK, 2019; pp. 281–296. [Google Scholar]
- Breth, H.; Amann, P. Time-settlement and Settlement Distribution with Depth in Frankfurt Clay; Session III/1; COSOS; British Geotechnical Society, Pentech. Press: London, UK, 1975; pp. 141–154. [Google Scholar]

**Figure 2.**Geomorphology map of Ville San Pietro (adapted from [21]).

**Figure 9.**Permanent Scatter positions and velocities (projected along the slope) at Ville San Pietro.

**Figure 11.**(

**a**) 3D model of the slope with the church load; (

**b**) Comparison between the detected stratigraphy profile (image above) and the numerical model cross-section (image below).

**Figure 12.**Groundwater level rise occurred from January 2018 to March 2018: comparison between real and simulated horizontal displacements at inclinometer I2, I3 and I4.

**Figure 14.**Comparison between the provided shear band evaluated on the basis of the geotechnical tests (image above) and the results of the numerical analysis obtained by PLAXIS (image below).

**Figure 15.**March 2018: Safety analysis displacements and depth of the shear band at inclinometer I2, I3 and I4.

**Figure 16.**Groundwater level fall occurred from March 2018 to June 2018: comparison between real and simulated horizontal displacements at inclinometer I3.

**Figure 21.**Inclinometer I3: comparison between the real displacements and the numerical results (with and without the church load).

Specimen 1 | Specimen 2 | Specimen 3 | ||
---|---|---|---|---|

H [cm] | Specimen height | 2.31 | 2.31 | 2.31 |

D [cm] | Specimen diameter | 6.00 | 6.00 | 6.00 |

Velocity [mm/min] | Applied shear velocity | 0.005 | 0.005 | 0.005 |

σ_{v} [kPa] | Vertical stress | 50.00 | 100.00 | 200.00 |

ΔH_{c} [mm] | Vertical consolidation shortening | 0.74 | 0.96 | 1.29 |

ΔH_{f} [mm] | Vertical failure shortening | 0.07 | 0.16 | 0.22 |

d_{h} [mm] | Horizontal failure displacement | 1.26 | 4.11 | 2.60 |

τ_{f} [kPa] | Failure shear stress | 39.20 | 63.00 | 130.70 |

Materials [-] | Volume Unit Weight [kN/m ^{3}] | Materials [-] | Surface Unit Weight [kN/m ^{2}] |
---|---|---|---|

Concrete | 24 | Tiles | 0.80 |

Slate | 27 | ||

Limestone | 26 | ||

Marble | 27 | ||

Stone and mortar wall | 22 |

Soil Properties | Blanket | Bedrock |
---|---|---|

${\gamma}_{dry}$ [kN/m^{3}] | 18 | 27 |

${\gamma}_{sat}$ [kN/m^{3}] | 21 | 30 |

φ′ [°] | 28 | 35 |

c′ [kPa] | 8 | 10 |

v [-] | 0.30 | 0.30 |

E [kPa] | 107,339 | 4,953,530 |

G [kPa] | 41,284 | 1,905,204 |

${K}_{0}$ [-] | 0.43 | 0.43 |

Soil Properties | Blanket | Bedrock |
---|---|---|

${\gamma}_{dry}$ [kN/m^{3}] | 18 | 27 |

${\gamma}_{sat}$ [kN/m^{3}] | 21 | 30 |

φ′ [°] | 28 | 35 |

c′ [kPa] | 8 | 10 |

v [-] | 0.30 | 0.30 |

E [kPa] | --- | 4,953,530 |

G [kPa] | --- | 1,905,204 |

${E}_{50}^{ref}$ [kPa] | 40,000 | --- |

${E}_{oed}^{ref}$ [kPa] | 20,000 | --- |

${E}_{ur}^{ref}$ [kPa] | 120,000 | --- |

m [-] | 0.70 | --- |

${K}_{0}$ [-] | 0.43 | 0.43 |

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**MDPI and ACS Style**

Bovolenta, R.; Bianchi, D. Geotechnical Analysis and 3D Fem Modeling of Ville San Pietro (Italy). *Geosciences* **2020**, *10*, 473.
https://doi.org/10.3390/geosciences10110473

**AMA Style**

Bovolenta R, Bianchi D. Geotechnical Analysis and 3D Fem Modeling of Ville San Pietro (Italy). *Geosciences*. 2020; 10(11):473.
https://doi.org/10.3390/geosciences10110473

**Chicago/Turabian Style**

Bovolenta, Rossella, and Diana Bianchi. 2020. "Geotechnical Analysis and 3D Fem Modeling of Ville San Pietro (Italy)" *Geosciences* 10, no. 11: 473.
https://doi.org/10.3390/geosciences10110473