• Geomechanics and Engineering
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• v.14 no.1
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• pp.9-17
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• 2018

Brazilian splitting tests, uniaxial compression tests and triaxial compression tests are carried out on the coal samples cored from Shanxi group $II_1$ coal seam of Jiaozuo coal mine, Henan province, China, to obtain their property parameters. Considering the bedding has notable effect on the property parameter of coal, the samples with different bedding angles are prepared. The effects of bedding on the anisotropic characteristics of the coal seam are investigated. A geological geomechanical model is built based on the geology characteristics of the Jiaozuo coal mine target reservoir to study the effects of bedding on the fracture propagations during hydraulic fracturing. The effects of injection pressure, well completion method, in-situ stress difference coefficient, and fracturing fluid displacement on the fracture propagations are investigated. Results show bedding has notable effects on the property parameters of coal, which is the key factor affecting the anisotropy of coal. The hydraulic cracks trends to bifurcate and swerve at the bedding due to its low strength. Induced fractures are produced easily at the locations around the bedding. The bedding is beneficial to form a complicated fracture network. Experimental and numerical simulations can help to understand the effects of bedding on hydraulic fracturing in coalbed methane reservoirs.

• Proceedings of the Korean Geotechical Society Conference
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• 2010.09a
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• pp.416-422
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• 2010

Estimating condition of geotechnical structures are difficult because of nonlinear time dependency and seasonal effects. Measuring data of structure failure is highly variable in time and space, and a unique approach cannot be defined to model structure movements. Characteristics of movements are obtained by using a statistical method called Principal Component Analysis(PCA). The PCA is a non-parametric method to separate unknown, statistically uncorrelated source processes from observed mixed processes. Instead, since the "best" mathematical relationship is estimated for given data sets of the input and output measured from target systems. As a consequence, this method is advantageous in modeling systems whose geomechanical properties are unknown or difficult to be measured.

• Geomechanics and Engineering
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• v.19 no.6
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• pp.523-532
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• 2019

Based on the formation characteristics, wellbore parameters and insulated tubing (IT) parameters of the Shengli oilfield, Shandong, China, a geomechanical model is built to predict the temperature distributions of the wellbore and formation. The effects of the IT heat conductivity coefficient (HCC), well depth and IT joint on the temperature distribution of the IT, completion casing, cement sheath, and formation are investigated. Results show the temperature of the formation around the wellbore has an exponentially decreasing relation with the distance to the wellbore. The temperature of the formation around the wellbore has an inverse relation with the IT HCC when the temperatures of the steam and the formation are given. The temperature of the casing outer wall is mainly determined by the steam temperature and IT HCC rather than by the initial formation temperature. The temperature of the casing at the IT joint is much larger than that of the other location. Due to the IT joint having a small size, the effects of the IT joint on the casing temperature distribution are limited to a small area only.

• Interaction and multiscale mechanics
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• v.4 no.1
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• pp.49-64
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• 2011

A methodology for jointed rock mass characterization starts with a research based on geological data and tests in order to define the geotechnical models used to support the decision about location, orientation and shape of cavities. Afterwards a more detailed characterization of the rock mass is performed allowing the update of the geomechanical parameters defined in the previous stage. The observed results can be also used to re-evaluate the geotechnical model using inverse methodologies. Cases of large underground structures modeling are presented. The first case concerns the modeling of cavities in volcanic formations. Then, an application to a large station from the Metro do Porto project developed in heterogeneous granite formations is also presented. Finally, the last case concerns the modeling of large cavities for a hydroelectric powerhouse complex. The finite element method and finite difference method software used is acquired from Rocscience and ITASCA, respectively.

• Geomechanics and Engineering
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• v.29 no.2
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• pp.113-131
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• 2022

A rockburst is a common disaster in deep-tunnel excavation engineering, especially for high-geostress areas. An anomalously low friction effect is one of the most important inducements of rockbursts. To elucidate the correlation between an anomalously low friction effect and a rockburst, we establish a two-dimensional prediction model that considers the discontinuous structure of a rock mass. The degree of freedom of the rotation angle is introduced, thus the motion equations of the blocks under the influence of a transient disturbing force are acquired according to the interactions of the blocks. Based on the two-dimensional discontinuous block model of deep rock mass, a rockburst prediction model is established, and the initiation process of ultra-low friction rockburst is analyzed. In addition, the intensity of a rockburst, including the location, depth, area, and velocity of ejection fragments, can be determined quantitatively using the proposed prediction model. Then, through a specific example, the effects of geomechanical parameters such as the different principal stress ratios, the material properties, a dip of principal stress on the occurrence form and range of rockburst are analyzed. The results indicate that under dynamic disturbance, stress variation on the structural surface in a deep rock mass may directly give rise to a rockburst. The formation of rockburst is characterized by three stages: the appearance of cracks that result from the tension or compression failure of the deformation block, the transformation of strain energy of rock blocks to kinetic energy, and the ejection of some of the free blocks from the surrounding rock mass. Finally, the two-dimensional rockburst prediction model is applied to the construction drainage tunnel project of Jinping II hydropower station. Through the comparison with the field measured rockburst data and UDEC simulation results, it shows that the model in this paper is in good agreement with the actual working conditions, which verifies the accuracy of the model in this paper.

• Geomechanics and Engineering
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• v.36 no.2
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• pp.111-119
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• 2024

In the realm of rock excavation projects, precise estimation of the drilling rate index stands as a pivotal factor in strategic planning and cost assessment. This study introduces and evaluates two pioneering computational intelligence models designed for the prognostication of the drilling rate index, a pivotal parameter with direct implications for cost estimation in rock excavation projects. These models, denoted as the Relevance Vector Regression (RVR) optimized with the Invasive Weed Optimization algorithm (IWO) (RVR-IWO model) and the RVR integrated with the Shuffled Frog Leaping algorithm (SFL) (RVR-SFL model), represent a groundbreaking approach to forecasting drilling rate index. The RVR-IWO and RVR-SFL models were meticulously devised to harness the capabilities of computational intelligence and optimization techniques for drilling rate index estimation. This research pioneers the integration of IWO and SFL with RVR, constituting an unprecedented effort in forecasting drilling rate index. The primary objective of this study was to gauge the precision and dependability of these models in forecasting the drilling rate index, revealing significant distinctions between the two. In terms of predictive precision, the RVR-IWO model emerged as the superior choice when compared to the RVR-SFL model, underscoring the remarkable efficacy of the Invasive Weed Optimization algorithm. The RVR-IWO model delivered noteworthy results, boasting a Variance Account for (VAF) of 0.8406, a Mean Squared Error (MSE) of 0.0114, and a Squared Correlation Coefficient (R²) of 0.9315. On the contrary, the RVR-SFL model exhibited slightly lower precision, yielding an MSE of 0.0160, a VAF of 0.8205, and an R2 of 0.9120. These findings serve to highlight the potential of the RVR-IWO model as a formidable instrument for drilling rate index prediction, particularly within the framework of rock excavation projects. This research not only makes a significant contribution to the realm of drilling engineering but also underscores the broader adaptability of the RVR-IWO model in tackling an array of challenges within the domain of rock engineering. Ultimately, this study advances the comprehension of drilling rate index estimation and imparts valuable insights into the practical implementation of computational intelligence methodologies within the realm of engineering projects.

• Geomechanics and Engineering
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• v.36 no.5
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• pp.465-474
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• 2024

Uniaxial compressive strength (UCS) is a critical geomechanical parameter that plays a significant role in the evaluation of rocks. The practice of indirectly estimating said characteristics is widespread due to the challenges associated with obtaining high-quality core samples. The primary aim of this study is to investigate the feasibility of utilizing the gene expression programming (GEP) technique for the purpose of forecasting the UCS for various rock categories, including Schist, Granite, Claystone, Travertine, Sandstone, Slate, Limestone, Marl, and Dolomite, which were sourced from a wide range of quarry sites. The present study utilized a total of 170 datasets, comprising Schmidt hammer (SH), porosity (n), point load index (Is(50)), and P-wave velocity (Vp), as the effective parameters in the model to determine their impact on the UCS. The UCS parameter was computed through the utilization of the GEP model, resulting in the generation of an equation. Subsequently, the efficacy of the GEP model and the resultant equation were assessed using various statistical evaluation metrics to determine their predictive capabilities. The outcomes indicate the prospective capacity of the GEP model and the resultant equation in forecasting the unconfined compressive strength (UCS). The significance of this study lies in its ability to enable geotechnical engineers to make estimations of the UCS of rocks, without the requirement of conducting expensive and time-consuming experimental tests. In particular, a user-friendly program was developed based on the GEP model to enable rapid and very accurate calculation of rock's UCS, doing away with the necessity for costly and time-consuming laboratory experiments.

• Proceedings of the Korean Geotechical Society Conference
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• 2010.03a
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• pp.1358-1365
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• 2010

Estimating condition of slope is difficult because of nonlinear time dependency and seasonal effects, which affect the displacements. Displacements and displacement patterns of landslides are highly variable in time and space, and a unique approach cannot be defined to model landslide movements. Characteristics of movements are obtained by using a statistical method called Principal Component Analysis(PCA). The PCA is a non-parametric method to separate unknown, statistically uncorrelated source processes from observed mixed processes. In the non-parametric approaches, no physical assumptions of target systems are required. Instead, since the "best" mathematical relationship is estimated for given data sets of the input and output measured from target systems. As a consequence, non-parametric approaches are advantageous in modeling systems whose geomechanical properties are unknown or difficult to be measured. Non-parametric approaches are consequently more flexible in modeling than parametric approaches. This method is expected to be a useful tool for the slope management of and alarm systems.

• Geomechanics and Engineering
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• v.14 no.1
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• pp.19-27
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• 2018

It follows from the basic principles of mechanics of deformable solids relating to the strength, stability and propagation of elastic waves that the Earth's inner core cannot exist in the form of a spherical structure in the assumed thermobaric conditions and calculation values of physico-mechanical parameters. Pressure level reaches a value that is significantly greater than the theoretical limit of medium strength in the model approximations at the surface of the sphere of the inner core. On the other hand, equilibrium state of the sphere is unstable on the geometric forming at much lower loads under the influence of the "dead" surface loads. In case of the action of "follower" loads, the assumed pressure value on the surface of the sphere is comparable with the value of the critical load of "internal" instability. In these cases, due to the instability of the equilibrium state, propagation of homogeneous deformations becomes uneven in the sphere. Moreover, the elastic waves with actual velocity cannot propagate in such conditions in solid medium. Violation of these fundamental conditions of mechanics required in determining the physical and mechanical properties of the medium should be taken into account in the integrated interpretations of seismic and laboratory (experimental) data. In this case, application of the linear theory of elasticity and elastic waves does not ensure the reliability of results on the structure and composition of the Earth's core despite compliance with the required integral conditions on the mass, moment of inertia and natural oscillations of the Earth.

• Journal of the Korean GEO-environmental Society
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• v.24 no.9
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• pp.41-46
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• 2023

Numerical analysis of frost heave is challenging due to the influence of soil and environmental factors. Thermo-hydromechanical coupled analysis relies heavily on excessive input variables and primarily focuses on validating clayey soils, so it is limited to frost susceptible silty soils. An empirical approach based on thermodynamics offers relatively simple frost heave analysis and the advantage of linking constitutive equations with frost heave to enable geomechanical interpretations. In this paper, we introduce an empirical numerical model using the Segregation Potential (SP) and evaluate reliability through comparative analysis with experimental results of frost susceptible silty soils. While the SP model enables frost heave analysis for the given silty soils, further investigation on various silty soils is necessary to gather data on key input variables.