Spatial correlation between landslides and geotechnical factors using Random Forest and SHAP

Due to the fact that the estimation of the rock mass properties is very important in any geotechnical project, many studies have become with the aim of their determination. But, the immediate determination is very difficult because the in situ tests are time-consuming, expensive and sometimes unreliable. For this reason, many researches have attempted to calculate the rock mass characteristic through empirical equations, but only few have focused on the ultramafic rocks. The main purpose of this study is to estimate the engineering properties of the ultramafic rock masses through the uniaxial compressive strength of the intact rock, the influence of blast damage, the material constant and the Geological Strength Index with the use of Hoek and Brown criterion (Roclab Software). Thus, sixteen samples, taken from central Greece (the western part of Othrys mt and the Kallidromo mt), were tested (uniaxial compressive strength and triaxial tests) and the results were statistically described and analysed. The manuscript reveals strong positive linear correlation between the estimated (through the Hoek and Brown failure criterion) uniaxial compressive strength and the measured (determined by strength tests) uniaxial compressive strength. The values of the uniaxial rock mass compressive strength, the global rock mass compressive strength, the rock mass tensile strength, and the rock mass modulus of deformation are finally calculated and presented. Furthermore, an attempt to correlate the rock mass deformation modulus (Erm) with the tangent young modulus (Ei) results that there is high correlation between them both for peridotites and serpentinites.

The process of evaluating rock mass strength requires that major structural features such as joints that influence rock strength are considered. In carbonate rock masses, however, the strength of the rock mass is largely dependent on intact rock strength and structural features play a secondary role. Laboratory experiments on porous rock have shown that intact rock strength reduces with increasing porosity, which has a direct effect on the rock mass strength. Rock porosity has however not been well accounted for in rock mass characterization methods currently in use. This research applies the modified GSI method for carbonate rock masses which is based on a combination of GSI and total porosity. The main aim is to quantify the GSI with respect to rock porosity which is a direct indicator of the state of karstification, as an inherent feature that affects rock mass strength. An empirical equation is proposed whereby the GSI as observed in the field is modified by a natural log of the value of porosity, giving rise to a modified GSI (GSIm). The GSIm together with laboratory properties of rock is used to determine the properties of Vipingo coral limestone from RocLab software. A deterministic parametric slope stability analysis is done using the finite element software Phase 2 with the rock mass properties as input parameters. The analysis results point to a direct dependence of the slope stability on slope angle, slope height and rock mass strength of the lithological unit. The graphs make a useful design guide for slopes engineered in this type of rock mass.

This paper presents the results of engineering geological investigations and determination of rock mass excavation methods in the main dam area of Matenggeng Dam. The study was carried out through engineering geological mapping, core drill evaluation and supported by laboratory test data. Classifications of rock masses were carried out based on the Geological Strength Index (GSI) and Rock Mass Rating (RMR) to analyze the excavation method. The results showed research area consisted of lithology in the form of andesite, intercalation sandstone - gravelly sandstone unit, intercalation sandstone - siltstone unit, and alluvium deposits. However, at the main dam area consists of lithology in the form of intercalation sandstone-siltstone unit and intercalation sandstone-gravelly sandstone unit. The rock masses at the main dam excavation line have a weathering degree from moderately to complately weathered. Intact rocks have Uniaxial Compressive Strength (UCS) values ranging from 1-50 Mpa and are a category of extremly weak to moderate rocks. The rock mass of intercalation sandstone-siltstone with very poor to poor quality (GSI (0 - 58), RMR (8 - 45)), and intercalation sandstone-gravelly sandstone with poor to fair quality (GSI (20 - 59), RMR (20 - 68)). The recommended rock excavation method based on the EXCASS System is diggir, easy ripper, and hard ripper.

Rock slopes stability is important for personnel and equipment safety in the open-pit mine. Instability and failure of slope occur due to many factors such as unsuited slope geometry, geological discontinuities, weak slope material due to weather influences. External loads such as high rainfall and seismicity could play an essential role in slope failure. Consequently, a precise classification of rock mass is needed for the basis of determining technical policy. Rock slopes in open pit coal mining areas, especially in Indonesia, are characterized by applying various rock mass classification systems, such as Rock Mass Rating (RMR) and Geological Strength Index (GSI), because the study area comprises well-exposed rock formations. In the RMR system, there are five main parameters i.e. Rock Quality Designation (RQD), Uniaxial Compressive Strength (UCS) of rocks, discontinuity spacing, discontinuity and groundwater conditions were considered. Several rock mass classification systems developed for the assessment of rock slope stability were evaluated with the condition of rock slopes in the tropics, especially Indonesian region, particularly in sedimentary rocks in the open pit coal mining area in order to get the corrected GSI equation used to characterize rock slopes based on rock mass structure quantitative analysis and discontinuities surface conditions. This paper provides correlation between the GSI and RMR for sediment rock in coal mines.

In this paper, an improved rock mass characterization method is presented. This method used a quantified geological strength index (GSI) and synthetic rock mass (SRM) model based on a discrete fracture network (DFN) and bonded particle model. A quantitative method is initially introduced to assist in the use of the conventional GSI chart, employing the rock block volume as the quantitative factor. The block volume for a given DFN model is calculated by a volumetric joint count, which is defined as the number of fractures intersecting a cube with unit length. The peak strength and deformation modulus of the rock mass are estimated based on the derived GSI, and then selected as references to constrain mechanical parameters of joints in the SRM model. A parametric study shows a positive correlation between the joint stiffness/friction coefficient and both the peak strength and deformation modulus. The joint friction coefficients of 0.5, 1.0, and 1.5 are suggested to correspond to the surface quality of ‘FAIR’, ‘GOOD’, and ‘VERY GOOD’ in the GSI chart. An advantage of the SRM over the GSI lies in the characterization of the post-peak strain softening behavior. The numerical results show that lower joint stiffness and friction coefficient result in a more ductile post-peak behavior. Additional SRM models with varied joint distributions show the complexities of rock mass characterization, where the rock mass strength, modulus, and post-peak strain softening rate may vary significantly with only one aspect of distributions of the joints, such as intensity or diameter. Triaxial testing is also conducted, and the SRM peak strengths are compared with the Hoek–Brown strength criterion based on the GSI system. The strengths of the regular triaxial models show general convergence with the Hoek–Brown criterion, but the strengths of the true triaxial models are less than those of the regular triaxial models due to deviatoric confining stresses. Meanwhile, ductile post-peak behavior is generally simulated in the triaxial testing. Cracking models are finally investigated and presented, behaving as additional information to explain the changes in the rock mass strength and deformability with different confining stresses. The method presented in this paper is meant to help geologists and engineers to quantify the GSI for jointed rock mass, and characterize the rock mass modulus and strength. Meanwhile, the synthetic rock mass method provides an alternative for rock mass characterization in addition to the traditional GSI method.

Rock mass strength is impacted by the coalignment of geological defects and intact rock (IR) bridges. The greater the alignment of geological defects and smaller the rock bridges, the weaker the rock mass strength. Current versions of the 1980s Hoek-Brown Method (HBM) for rock mass strength considers rock mass blockiness and defect condition via a Geological Strength Index (GSI) chart. This chart was refined several times, but these revisions still do not directly consider coaligned defects and bridges. Step-Path Method (SPM) evolved in mid-1970s to assess strength implications of coaligned defects and IR bridges. Early SPM models were simple; but progressively evolved to consider more complex situations. In late 1980s, computer software was written to assess rock mass shear strength by Monte-Carlo statistical simulation of defect and IR bridge along failure paths through slopes. Since mid-2000s, EXCEL spreadsheets have aided this type of assessment. SPM often computes a lower rock mass strength than HBM. Based on 230+ case studies an equation was proposed in 2019 to adjust the GSI index in HBM based on relative occurrences of coaligned defects and IR bridges along failure paths. The general equation is GSI Design = {GSI General Rock Mass – [0.4 x (% coaligned defects)] + [1.2 x (% IR bridges)]}. With the above adjusted GSI, HBM computes near-same rock mass strength as SPM. Appropriateness of above GSI adjustment equation with respect coaligned defects is checked by two-dimensional (2D) jointed finite element (FE) modelling. Results are presented and discussed. The method is presented for alternative strength inputs into jointed rock masses to account for the presence of co-aligned defects dipping into the excavated slope.

Rock abrasion plays a significant role in geotechnical design, tunneling operations and the safety of foundations from scour. It is imperative to determine such properties of uniaxial compression strength (UCS), rock quality designation (RQD) and hardness for rock engineering to help determine the amount of scour at foundation locations in order to prevent structural collapse, wear on drilling tools and help predict unstable rock conditions. Current practice for estimating maximum rock abrasion is based on the Los Angeles abrasion test; however, more research is needed to provide a more accurate and compatible method for all subsurface materials used in mining and civil engineering projects. This report will provide simple correlations relating abrasion resistance to RQD, UCS, Geological Strength Index (GSI) and Rock Mass Rating (RMR) and shear strength of metamorphic rock (Quartzite). Methods, results, recommendations and conclusions are presented. The paper also introduces recommendations for future rock abrasion techniques and discusses the use of these correlations exhibiting strong relationships between the mentioned rock properties.

ABSTRACT: The main classification systems that estimate rock mass properties include variants of the Rock Mass Rating (RMR) System, Rock Quality Designation (RQD), the Norwegian Tunneling Index (Q) (Barton), and the Geological Strength Index (GSI). The RMR system is based on intact strength, Rock quality designation, fracture frequency, and discontinuity condition. Typical distributions for these parameters may be approximated by normal, lognormal, or Weibull distributions and discrete distributions for fracture conditions. Water and pore pressure are sometimes included but should generally be treated as a boundary condition. RQD is a single-parameter system describing the percentage of sound rock core with a length greater than 10 cm. The Barton system has three main terms to describe a relative measure of the block size, an indicator of the inter-block shear strength, and a third quotient to describe "active stresses." One of the primary findings of the statistical study is that two parameter systems, such as blockiness and joint condition, are better differentiators between rock mass classes; however, these systems still smear parameters. For example, a GSI range of 25-55 each indicates anything from blocky to disintegrated rock mass conditions. As a result, strength estimators based on GSI are not reliable for estimating rock mass strength and, in turn, the factor of safety. RMR and GSI results result in values on a normal distribution scaled from 0-100, typically centered on 50. The models are insufficient to describe the tail end of the distribution where rock mass failure typically occurs. The Q system significantly improves when the terms are derived independently but suffers from the same normalization issue when calculated from an RMR value. The surprising finding is that single-parameter systems, including Fracture Frequency and Volumetric joint count, are better estimators (and differentiators) or properties across the range of rock mass conditions when looked at individually. Always understand the range of the rock mass parameters used and how that can impact the design. The paper will evaluate the need to develop strength estimators based on fracture frequency and volumetric joint count. Rock mass strength estimates should be developed from the underlying input data for classification rather than from normalized sums of multiple parameters.

The aim of this paper was to study the influence of the footing shape and the effect of the roughness of the foundation base on the bearing capacity of shallow foundations on rock masses. For this purpose the finite difference method was used to analyze the bearing capacity of various types and states of rock masses under the assumption of Hoek-Brown failure criterion, for both plane strain and axisymmetric model, and considering smooth and rough interface. The results were analyzed based on a sensitivity study of four varying parameters: foundation width, rock material constant (mo), uniaxial compressive strength and geological strength index. Knowing how each parameter influences the bearing capacity depending on the footing shape (circular vs strip footing) and the footing base interface roughness (smooth vs rough), two correlation factors were developed to estimate the percentage increase of the ultimate bearing capacity as a function of the footing shape and the roughness of the footing base interface.

Calculation of the bearing capacity of shallow foundations on rock masses is usually addressed either using empirical equations, analytical solutions, or numerical models. While the empirical laws are limited to the particular conditions and local geology of the data and the application of analytical solutions is complex and limited by its simplified assumptions, numerical models offer a reliable solution for the task but require more computational effort. This research presents an artificial neural network (ANN) solution to predict the bearing capacity due to general shear failure more simply and straightforwardly, obtained from FLAC numerical calculations based on the Hoek and Brown criterion, reproducing more realistic configurations than those offered by empirical or analytical solutions. The inputs included in the proposed ANN are rock type, uniaxial compressive strength, geological strength index, foundation width, dilatancy, bidimensional or axisymmetric problem, the roughness of the foundation-rock contact, and consideration or not of the self-weight of the rock mass. The predictions from the ANN model are in very good agreement with the numerical results, proving that it can be successfully employed to provide a very accurate assessment of the bearing capacity in a simpler and more accessible way than the existing methods.

A new method to promptly evaluate spatial earthquake probability mapping using an explainable artificial intelligence (XAI) model

In this paper, the quantitative Geological Strength Index (GSI) for Singapore’s sedimentary rock mass is determined by applying four different approaches proposed by Hoek et al. (Quantification of the geological strength index chart, 2013), Cai et al. (Int J Rock Mech Min Sci 41(1):3–49, 2004), Sonmez and Ulusay (Int J Rock Mech Min Sci 36:743–760, 1999) and Russo (Improving the reliability of GSI estimation: the integrated GSI-RMi system, 2009) respectively. The relevant rock mass properties, including blockiness and discontinuities surface conditions, of 420 excavated rock faces in a Singapore’s underground excavation project are assessed for such determination. The results obtained by these different approaches are observed falling approximately in the same range between 45 and 55. Moreover, those quantitative GSI results are in good correlation with qualitative GSI which were assessed on excavated rock faces using Hoek et al. (Support of underground excavations in hard rock, Balkema, Rotterdam, 1995) approach. This study demonstrates that the four different approaches perform well by giving similar range of results, although different input parameters are applied in the calculation. A new GSI relationship between joint condition factor Bieniawski (Engineering rock mass classification, Wiley, New York, 1989) and RQD (rock quality designation) is also proposed to better match the qualitative GSI values.

The Geological Strength Index (GSI) is a system of rock mass characterization that has been developed in engineering rock mechanics to meet the need for reliable input data related to rock mass properties required as input for numerical analysis or closed-form solutions for designing tunnels, slopes, or foundations in rocks. The geological character of the rock material, together with the visual assessment of the mass it forms, is used as a direct input for the selection of parameters for predicting rock mass strength and deformability. This approach enables a rock mass to be considered as a mechanical continuum without losing the influence that geology has on its mechanical properties. It also provides a field method for characterizing difficult-to-describe rock masses. Recommendations on the use of GSI are given and, in addition, cases where the GSI is not applicable are discussed.

Indonesian government through the National Atomic Energy Agency has planned to build a nuclear power plant. One of the proposed sites is in West Bangka Regency, Bangka Belitung Archipelago Province. The engineering geology of this area is, however, not fully understood and requires further investigations. Engineering geology investigations were carried out by assessing the rock mass quality and bearing capacity based on field observation and drilling data. The assessment was conducted using Rock Mass Rating (RMR) and Geological Strength Index (GSI) classification. The rock mass in the study area was divided into four units, namely Units of Sandstone, Granite, Mudstone and Pebbly Sandstone. The RMR and GSI values in the study area are influenced by the parameters of discontinuity space density, the slope of discontinuity orientation, grade of weathering and groundwater conditions. The assessment shows that the Granite Unit has the best quality which is shown by the average RMR value of 53 and GSI value of 66. Based on the average RMR value, the Granite Unit is estimated to have cohesion value between 0.2 and 0.3 MPa, friction angle between 25° and 35°, and allowable bearing pressure between 280 and 135 T/m2. Based on the GSI value, the Granite Unit is estimated to have uniaxial compressive strength value between 1.0465 and 183.8 MPa, tensile strength between (-0.0122) and (-5.2625) MPa, rock mass strength values between 24.5244 and 220.351 MPa, and modulus of deformation within a range of 1.73–86.68 GPa. The Granite Unit is considered to be the most appropriate location for the nuclear power plants. Keywords: Nuclear power plant foundation, geological strength index, rock mass rating, rock mass quality

In order to obtain the accurate mechanical parameters of deep‐buried coal goaf rock mass, the limitation of geological strength index (GSI) in concealed rock mass is analyzed. Based on the test result and analysis of the current normative standards, the classification indexes of rock mass structural are optimized based on discontinuity distance d and rock mass integrity index Kv. The ratio of rock mass saturated strength to dry strength, η, is introduced, quantization formula of structural surface conditions is proposed, and the influence of groundwater and rock types is included in structural surface condition classification. The GSI system is improved to better suit all types of deep‐buried and water‐rich rock masses. Furthermore, the rock mass disturbance factor D’s quantitative formula is listed according to the Hoek–Brown (HB) criterion. Taking the goaf roof under railway as an example, the parameters of deep‐buried rock mass are obtained based on the improved quantitative GSI system and HB criterion. This research provides a scientific reference for achieving geological parameters and engineering designing in goaf areas.