• Geomechanics and Engineering
• /
• 제37권4호
• /
• pp.307-321
• /
• 2024

This paper delves into the critical assessment of predicting sidewall displacement in underground caverns through the application of nine distinct machine learning techniques. The accurate prediction of sidewall displacement is essential for ensuring the structural safety and stability of underground caverns, which are prone to various geological challenges. The dataset utilized in this study comprises a total of 310 data points, each containing 13 relevant parameters extracted from 10 underground cavern projects located in Iran and other regions. To facilitate a comprehensive evaluation, the dataset is evenly divided into training and testing subset. The study employs a diverse array of machine learning models, including recurrent neural network, back-propagation neural network, K-nearest neighbors, normalized and ordinary radial basis function, support vector machine, weight estimation, feed-forward stepwise regression, and fuzzy inference system. These models are leveraged to develop predictive models that can accurately forecast sidewall displacement in underground caverns. The training phase involves utilizing 80% of the dataset (248 data points) to train the models, while the remaining 20% (62 data points) are used for testing and validation purposes. The findings of the study highlight the back-propagation neural network (BPNN) model as the most effective in providing accurate predictions. The BPNN model demonstrates a remarkably high correlation coefficient (R2 = 0.99) and a low error rate (RMSE = 4.27E-05), indicating its superior performance in predicting sidewall displacement in underground caverns. This research contributes valuable insights into the application of machine learning techniques for enhancing the safety and stability of underground structures.

• Advances in nano research
• /
• 제16권5호
• /
• pp.473-487
• /
• 2024

The current study employs the nonlocal Timoshenko beam (NTB) theory and von-Kármán's geometric nonlinearity to develop a non-classic beam model for evaluating the nonlinear free vibration of bi-directional functionally-graded (BFG) nanobeams. In order to avoid the stretching-bending coupling in the equations of motion, the problem is formulated based on the physical middle surface. The governing equations of motion and the relevant boundary conditions have been determined using Hamilton's principle, followed by discretization using the differential quadrature method (DQM). To determine the frequencies of nonlinear vibrations in the BFG nanobeams, a direct iterative algorithm is used for solving the discretized underlying equations. The model verification is conducted by making a comparison between the obtained results and benchmark results reported in prior studies. In the present work, the effects of amplitude ratio, nanobeam length, material distribution, nonlocality, and boundary conditions are examined on the nonlinear frequency of BFG nanobeams through a parametric study. As a main result, it is observed that the nonlinear vibration frequencies are greater than the linear vibration frequencies for the same amplitude of the nonlinear oscillator. The study finds that the difference between the dimensionless linear frequency and the nonlinear frequency is smaller for CC nanobeams compared to SS nanobeams, particularly within the α range of 0 to 1.5, where the impact of geometric nonlinearity on CC nanobeams can be disregarded. Furthermore, the nonlinear frequency ratio exhibits an increasing trend as the parameter µ is incremented, with a diminishing dependency on nanobeam length (L). Additionally, it is established that as the nanobeam length increases, a critical point is reached at which a sharp rise in the nonlinear frequency ratio occurs, particularly within the nanobeam length range of 10 nm to 30 nm. These findings collectively contribute to a comprehensive understanding of the nonlinear vibration behavior of BFG nanobeams in relation to various parameters.

• Advances in nano research
• /
• 제16권5호
• /
• pp.509-519
• /
• 2024

In this study, the static analysis of carbon nanotube-reinforced composites (CNTRC) beams resting on a Winkler-Pasternak elastic foundation is presented. The developed theories account for higher-order variation of transverse shear strain through the depth of the beam and satisfy the stress-free boundary conditions on the top and bottom surfaces of the beam. To study the effect of carbon nanotubes distribution in functionally graded (FG-CNT), we introduce in the equation of CNT volume fraction a new exponent equation. The SWCNTs are assumed to be aligned and distributed in the polymeric matrix with different patterns of reinforcement. The rule of mixture is used to describe the material properties of the CNTRC beams. The governing equations were derived by employing Hamilton's principle. The models presented in this work are numerically provided to verify the accuracy of the present theory. The analytical solutions are presented, and the obtained results are compared with the existing solutions to verify the validity of the developed theories. Many parameters are investigated, such as the Pasternak shear modulus parameter, the Winkler modulus parameter, the volume fraction, and the order of the exponent in the volume fraction equation. New results obtained from bending and stresses are presented and discussed in detail. From the obtained results, it became clear the influence of the exponential CNTs distribution and Winkler-Pasternak model improved the mechanical properties of the CNTRC beams.

• 한국지하수토양환경학회지:지하수토양환경
• /
• 제29권3호
• /
• pp.23-36
• /
• 2024

Miryang City, the study area, has a water supply rate of 87.4%, which is 12% lower than the national water supply rate of 99.4%, but has a high dependence on groundwater due to the high ratio of farms. In agricultural areas, contamination becomes relatively more critical, requiring significant attention to the management and conservation of groundwater resources. This study aims at estimate groundwater vulnerability of Miryang City using the DRASTIC index map, Piper diagram, and water quality data to correlated with the DRASTIC index. The results from DRASTIC map were divided into five classes: very high, high, moderate, low, and very low. The areas in central and southern part of study area, which are characterize by a very high index with [Ca-Cl] and [Na-Cl] water types, covering a large alluvium with the Miryang River and Nakdonggang River. In addition, a correlation analysis between groundwater quality parameters and the DRASTIC index was carried out. Chloride, sodium, and sulfate ions showed a weak relationship with DRASTIC index, with correlation coefficient was 0.507, 0.487 and 0.344, respectively. These results suggest that aquifer media, soil media, hydraulic conductivity, and chloride ion are important factors for groundwater vulnerability.

• Imaging Science in Dentistry
• /
• 제54권2호
• /
• pp.121-127
• /
• 2024

Purpose: Preoperative identification of the intraosseous posterior superior alveolar artery (PSAA) is critical when planning sinus surgery. This study was conducted to determine the distance between the cementoenamel junction and the PSAA, as well as to identify factors influencing the detection of the PSAA on cone-beam computed tomography (CBCT). Materials and Methods: In total, 254 CBCT scans of maxillary sinuses, acquired with 2 different scanners, were examined to identify the PSAA. The distance from the cementoenamel junction (CEJ) to the PSAA was recorded at each maxillary posterior tooth position. Binomial logistic regression and multiple linear regression were employed to evaluate the effects of scanner type, CBCT parameters, sex, and age on PSAA detection and CEJ-PSAA distance, respectively. P-values less than 0.05 were considered to indicate statistical significance. Results: The mean CEJ-PSAA distances at the second molar, first molar, second premolar, and first premolar positions were 17.0±4.0 mm, 21.8±4.1 mm, 19.5±4.7 mm, and 19.9±4.9 mm for scanner 1, respectively, and 17.3±3.5 mm, 16.9±4.3 mm, 18.5±4.1 mm, and 18.4±4.3 mm for scanner 2. No independent variable significantly influenced PSAA detection. However, tooth position (b=-0.67, P<0.05) and scanner type (b=-1.3, P<0.05) were significant predictors of CEJ-PSAA distance. Conclusion: CBCT-based estimates of CEJ-PSAA distance were comparable to those obtained in previous studies involving cadavers, CT, and CBCT. The type of CBCT scanner may slightly influence this measurement. No independent variable significantly impacted PSAA detection.

• Journal of Plant Biotechnology
• /
• 제50권
• /
• pp.183-189
• /
• 2023

This study investigated the impact of two distinct MS basal media: one containing FeNaEDTA and the other FeEDDHA, on the growth of five unique gerbera cultivars (Shy Pink, Pink Holic, Breeze, Harmony, Snow Dream). Notably, the response to these media types varied significantly among the cultivars, particularly concerning leaf yellowing and plant growth. 'Shiny Pink' and 'Pink Holic' exhibited leaf yellowing on the FeNaEDTA-containing medium but displayed leaf greening on the FeEDDHA-containing medium. In contrast, 'Snow Dream,' 'Harmony,' and 'Breeze' remained unaffected on both medium types. However, the FeNaEDTA-containing medium promoted higher plant height and petiole length in 'Breeze,' 'Harmony,' and 'Snow Dream' than the FeNaEDTA-containing medium did. A promotive effect of silver nanoparticles (AgNPs) on plant growth and leaf greening was observed in 'Pink Holic,' particularly on the FeNaEDTA-containing medium, while the addition of AgNPs to the FeEDDHA-containing medium negatively affected plant growth. These results highlight the substantial influence of medium type, specifically the presence of FeNaEDTA or FeEDDHA, on gerbera growth responses, emphasizing the critical role of medium selection in gerbera propagation. Additionally, when contemplating the addition of AgNPs for in vitro gerbera propagation, it is crucial to consider the medium type.

• ALGAE
• /
• 제39권2호
• /
• pp.109-127
• /
• 2024

High production and efficient harvesting of microalgae containing high omega-3 levels are critical concerns for industrial use. Aeration can elevate production of some microalgae by providing CO₂ and O₂. However, it may lower the production of others by generating shear stress, causing severe cell damage. The mixotrophic dinoflagellate Gymnodinium smaydae is a new, promising microalga for omega-3 fatty acid production owing to its high docosahexaenoic acid content, and determining optimal conditions and methods for high omega-3 fatty acid production and efficient harvest using G. smaydae is crucial for its commercial utilization. Therefore, to determine whether continuous aeration is required, we measured densities of G. smaydae and the dinoflagellate prey Heterocapsa rotundata in a 100-L semi-continuous cultivation system under no aeration and continuous aeration conditions daily for 9 days. Furthermore, to determine the optimal conditions for harvesting through centrifugation, different rotational speeds of the continuous centrifuge and different flow rates of the pump injecting G. smaydae + H. rotundata cells into the centrifuge were tested. Under continuous aeration, G. smaydae production gradually decreased; however, without aeration, the production remained stable. Harvesting efficiency and the dry weights of omega-3 fatty acids of G. smaydae + H. rotundata cells at a rotational speed of 16,000 rpm were significantly higher than those at 2,000-8,000 rpm. However, these parameters did not significantly differ at injection pump flow rates of 1.0-4.0 L min^-1. The results of the present study provide a basis for optimized production and harvest conditions for G. smaydae and other microalgae.

• Earthquakes and Structures
• /
• 제26권3호
• /
• pp.203-218
• /
• 2024

Beam-column joints in the frame structure are at high risk of brittle shear failure which would lead to significant residual deformation and even the collapse of the structure during an earthquake. In order to improve the damage issue and enhance the recoverability of the beam-column joints, a sector lead rubber damper (SLRD) has been developed. The SLRD can increase the bearing capacity and energy dissipation capacity, and also demonstrating recoverability of seismic performance following cyclic loading. In this paper, the hysteretic behavior of SLRD was experimentally investigated in terms of the regular hysteretic behavior, large deformation behavior and fatigue behavior. Furthermore, a parametric analysis was performed to study the influence of the primary design parameters on the hysteretic behavior of SLRD. The results show that SLRD resist the exerted loading through the shear capacity of both rubber parts coupled with the lead cores in the pre-yielding stage of lead cores. In the post-yielding phase, it is only the rubber parts of the SLRD that provide the shear capacity while the lead cores primarily dissipate the energy through shear deformation. The SLRD possesses a robust capacity for large deformation and can sustain hysteretic behavior when subjected to a loading rotation angle of 1/7 (equivalent to 200% shear strain of the rubber component). Furthermore, it demonstrates excellent fatigue resistance, with a degradation of critical behavior indices by no more than 15% in comparison to initial values even after 30 cycles. As for the designing practice of SLRD, it is recommended to adopt the double lead core scheme, along with a rubber material having the lowest possible shear modulus while meeting the desired bearing capacity and a thickness ratio of 0.4 to 0.5 for the thin steel plate.

• Geomechanics and Engineering
• /
• 제36권5호
• /
• pp.465-474
• /
• 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.

• Nuclear Engineering and Technology
• /
• 제56권5호
• /
• pp.1747-1753
• /
• 2024

The accurate determination of formation density and the physical properties of rocks is the most critical logging tasks which can be obtained using gamma-ray transport and detection tools. Though the simulation works published so far have considerably improved the knowledge of the parameters that govern the responses of the detectors in these tools, recent studies have found considerable differences between the results of using a conventional model of a homogeneous mixture of formation and fluid and an inhomogeneous fractured medium. It has increased concerns about the importance of the complexity of the model used for the medium in simulation works. In the present study, we have suggested two various models for the flow of the fluid in porous media and fractured rock to be used for logging purposes. For a typical gamma-gamma logging tool containing a ¹³⁷Cs source and two NaI detectors, simulated by using the MCNPX code, a simplified porous (SP) model in which the formation is filled with elongated rectangular cubes loaded with either mineral material or oil was investigated. In this model, the oil directly reaches the top of the medium and the connection between the pores is not guaranteed. In the other model, the medium is a large 3-D matrix of 1 cm³ randomly filled cubes. The designed algorithm to fill the matrix sites is so that this realistic random (RR) model provides the continuum growth of oil flow in various disordered directions and, therefore, fulfills the concerns about modeling the rock textures consist of extremely complex pore structures. For an arbitrary set of oil concentrations and various formation materials, the response of the detectors in the logging tool has been considered as a criterion to assess the effect of modeling for the distribution of pores in the formation on simulation studies. The results show that defining a RR model for describing heterogeneities of a porous medium does not effectively improve the prediction of the responses of logging tools. Taking into account the computational cost of the particle transport in the complex geometries in the Monte Carlo method, the SP model can be satisfactory for gamma-gamma logging purposes.