• Geomechanics and Engineering
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• v.34 no.6
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• pp.697-726
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• 2023

Brittleness as an important property of rock plays a crucial role both in the failure process of intact rock and rock mass response to excavation in engineering geological and geotechnical projects. Generally, rock brittleness indices are calculated from the mechanical properties of rocks such as uniaxial compressive strength, tensile strength and modulus of elasticity. These properties are generally determined from complicated, expensive and time-consuming tests in laboratory. For this reason, in the present research, an attempt has been made to predict the rock brittleness indices from simple, inexpensive, and quick laboratory test results namely dry unit weight, porosity, slake-durability index, P-wave velocity, Schmidt rebound hardness, and point load strength index using multiple linear regression, exponential regression, support vector machine (SVM) with various kernels, generating fuzzy inference system, and regression tree ensemble (RTE) with boosting framework. So, this could be considered as an innovation for the present research. For this purpose, the number of 39 rock samples including five igneous, twenty-six sedimentary, and eight metamorphic were collected from different regions of Iran. Mineralogical, physical and mechanical properties as well as five well known rock brittleness indices (i.e., B₁, B₂, B₃, B₄, and B₅) were measured for the selected rock samples before application of the above-mentioned machine learning techniques. The performance of the developed models was evaluated based on several statistical metrics such as mean square error, relative absolute error, root relative absolute error, determination coefficients, variance account for, mean absolute percentage error and standard deviation of the error. The comparison of the obtained results revealed that among the studied methods, SVM is the most suitable one for predicting B₁, B₂ and B₅, while RTE predicts B₃ and B₄ better than other methods.

• Journal of the Korean Geotechnical Society
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• v.23 no.4
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• pp.133-147
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• 2007

Downhole seismic method is very economic and easy of operation because it uses only one borehole and simple surface source to obtain the shear wave velocity ($V_s$) profile of a site. Even though it is widely used by the site investigation companies, universities and institutes, however, the $V_s$ profile determined by downhole seismic method has often low reliability due to employment of wrong combinations of field losing equipment and interpretation method and deficiency of experience. Round robin test was performed and testing equipment and procedure were compared. Adequate downhole seismic testing equipment was constructed based on the comparison and verification study of the round robin test. The data acquisition and software interpretation were also developed for automation and quick test in field. Finally, the effectiveness and applicability were verified through the field test by using the constructed testing system.

• Journal of Convergence for Information Technology
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• v.12 no.3
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• pp.151-157
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• 2022

The purpose of this study was to investigate the frequency characteristics of forced vibration considering the vehicle progress. And the vibration characteristics in frequency domain that occur, when vehicle passes the bump, were analyzed. The responses such as displacement, velocity and acceleration were obtained through numerical analysis, and FFT processing was performed to analyze the frequency response function(FRF) characteristics. In particular, the location of vehicle eigenmodes and external excitation modes was clearly shown and analyzed. In the forced vibration model by external force, the behavior of the eigenmode in power spectrum and real and imaginary parts were also analyzed. The mode characteristics were also analyzed in each FRF. It was approximated by assuming total excitation force by considering the exciting frequency using impulse and sine wave forces, which can give the amplitude and frequencies. The response characteristics of forced oscillations having different mass, damping and stiffness have been systematically discussed.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.6C
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• pp.241-253
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• 2010

For seismic design of a vertical shaft, three-dimensional Finite Element (FE) analyses were performed to evaluate the accurate response of a vertical shaft and to apply a Response Displacement Method (RDM). Special attention is given to the evaluation of seismic base and response displacement of surrounding soil, estimation of load and loading method. Based on the result, it was found that shear wave velocity of seismic base greater than 1500m/s was appropriate for the seismic design. It was also found that double cosine method which evaluates a response displacement of surrounding soil was most appropriate to consider the characteristic of multi-layered soil. Finally, shape effect of the structure was considered to clarify the dynamic behavior of vertical shaft and it would be more economical vertical shaft design when a vertical shaft was analyzed by using RDM.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.3C
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• pp.157-170
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• 2006

Downhole method is considered as giving a little unreliable Vs profile when the signal to noise ratio(S/N) is low and the travel time information is erroneous although it is economical and ease of operation. Direct method has been applied for obtaining adequate result in this case. But it is difficult to determine optimum result by using direct method which is subjective and considering straight ray path. Therefore, in this paper, Mean Refracted Ray Path Method(MRM) was proposed, which is automated and considering refracted ray path. Artificial travel time data adding some travel time error was generated by forward modeling based on Snell's Law and travel time data was also obtained from numerical signal traces using FEM modelling. Using these travel time data, reliability of MRM was verified in the manner of comparing the results determined by MRM with the model. Finally, proposed method was applied to the real field data and it was considered as improved method for obtaining the optimum result in downhole seismic method.

• Earthquakes and Structures
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• v.25 no.1
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• pp.27-41
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• 2023

This study focused on nonlinear effective stress site response analysis using two coupled constitutive models, that is, the DM model (Dafalias and Manzari 2004), which incorporated a simple plasticity sand model accounting for fabric change effects, and the PMDY03 model (Khosravifar et al. 2018), that is, a 3D model for earthquake-induced liquefaction triggering and postliquefaction response. A detailed parametric study was conducted to validate the effectiveness of nonlinear site response analysis and porewater pressure (PWP) generation through a true coupled formulation for assessing the initiation of liquefaction at ground level. The coupled models demonstrated accurate prediction of liquefaction triggering, which was in line with established empirical liquefaction triggering relations in published databases. Several limitations were identified in the evaluation of liquefaction using the cyclic stress method, despite its widespread implementation for calculating liquefaction triggering. Variations in shear stiffness, represented by changes in shear wave velocity (Vs1), exerted the most significant influence on site response. The study further indicated that substantial differences in response spectra between nonlinear total stress and nonlinear effective stress analyses primarily occurred when liquefaction was triggered or on the verge of being triggered, as shown by excess PWP ratios approaching unity. These differences diminished when liquefaction occurred towards the later stages of intense shaking. The soil response was predominantly influenced by the higher stiffness values present prior to liquefaction. A key contribution of this study was to validate the criteria used to assess the triggering of level-ground liquefaction using true coupled effective-stress constitutive models, while also confirming the reliability of numerical approximations including the PDMY03 and DM models. These models effectively captured the principal characteristics of liquefaction observed in field tests and laboratory experiments.

• Journal of the Korea Institute of Building Construction
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• v.23 no.6
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• pp.715-726
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• 2023

This study suggested that protective panels should be installed as sacrificial members as a safety design method for structures with potential explosions such as hydrogen charging stations to minimize direct damage to the structure and have resilience. To this end, the focus of the experiment is on quantitatively evaluating the impact of the structure when the protection panel is installed closely or spaced apart from the structure in a high-speed collision situation of the projectile. The experimental design used steel plates instead of concrete structural members mainly used in the past for excellent reproducibility, and the impact of structural members was compared and analyzed through deformation differences on the back of the steel plate. In addition, the impact of changes in the physical properties of the elastic body used as a separation material for the protective member and the difference in shock wave transmission time according to the protective member and the elastic body on the structural member was investigated.

• The Journal of the Acoustical Society of Korea
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• v.28 no.3
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• pp.260-267
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• 2009

It is very difficult to form a desired complex sound field at a designated region precisely as an application of acoustic arrays, which is one of important objects of array systems. To solve the problem, a filter design method was suggested, which employed the concept of an inverse method using the acoustical holography based on the boundary element method. In the acoustical holography used for the source identification, the measured field data are employed to reconstruct the vibro-acoustic parameters on the source surface. In the analogous problem of source array design, the desired field data at some specific points in the sound field was set as constraints and the volume velocity at the surface points of the source plane became the source signal to satisfy the desired sound field. In the filter design, the constraints for the desired sound field are set, first. The array source and given space are modelled by the boundary elements. Then, the desired source parameters are inversely calculated in a way similar to the holographic source identification method. As a test example, a target field comprised of a quiet region and a plane wave propagation region was simultaneously realized by using the array with 16 loudspeakers.

• 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.

• Geomechanics and Engineering
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• v.37 no.5
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• pp.475-498
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• 2024

The prediction of the susceptibility of soil to liquefaction using a limited set of parameters, particularly when dealing with highly unbalanced databases is a challenging problem. The current study focuses on different ensemble learning classification algorithms using highly unbalanced databases of results from in-situ tests; standard penetration test (SPT), shear wave velocity (V_s) test, and cone penetration test (CPT). The input parameters for these datasets consist of earthquake intensity parameters, strong ground motion parameters, and in-situ soil testing parameters. liquefaction index serving as the binary output parameter. After a rigorous comparison with existing literature, extreme gradient boosting (XGBoost), bagging, and random forest (RF) emerge as the most efficient models for liquefaction instance classification across different datasets. Notably, for SPT and V_s-based models, XGBoost exhibits superior performance, followed by Light gradient boosting machine (LightGBM) and Bagging, while for CPT-based models, Bagging ranks highest, followed by Gradient boosting and random forest, with CPT-based models demonstrating lower G_mean(error), rendering them preferable for soil liquefaction susceptibility prediction. Key parameters influencing model performance include internal friction angle of soil (ϕ) and percentage of fines less than 75 µ (F₇₅) for SPT and V_s data and normalized average cone tip resistance (q_c) and peak horizontal ground acceleration (a_max) for CPT data. It was also observed that the addition of V_s measurement to SPT data increased the efficiency of the prediction in comparison to only SPT data. Furthermore, to enhance usability, a graphical user interface (GUI) for seamless classification operations based on provided input parameters was proposed.