• Geomechanics and Engineering
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• v.34 no.3
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• pp.233-250
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• 2023

This paper investigates the flexural analysis of isotropic, transversely isotropic, and laminated composite plates using a new higher-order normal and shear deformation theory. In the present theory, only five unknown functions are involved compared to six or more unknowns used in the other similar theories. The developed theory does not need a shear correction factor. It can satisfy the zero traction boundary conditions on the top and the bottom surfaces of the plate as well as account for sufficient distribution of the transverse shear strains. The thickness stretching effect is considered in the computation. A simply supported was considered on all edges of the plate. The plate is subjected to uniform and sinusoidal distributed load in the static analysis. Laminated composite, isotropic, and transversely isotropic plates are considered. The governing equations are obtained utilizing the virtual work principle. The differential equations are solved via Navier's procedure. The results obtained from the developed theory are compared with other higher-order theories considered in the previous studies and 3D elasticity solutions. The results showed that the proposed theory accurately and effectively predicts the bidirectional bending responses of laminated composite plates. Several parametric studies are presented to illustrate the various parameters influencing the static response of the laminated composite plates.

• Smart Structures and Systems
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• v.32 no.5
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• pp.319-338
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• 2023

The study presents a new hybrid data-driven method by combining radial basis functions neural networks (RBF-NN) with the Jaya algorithm (JA) to provide effective structural health monitoring of arch dams. The novelty of this approach lies in that only one user-defined parameter is required and thus can increase its effectiveness and efficiency, as compared to other machine learning techniques that often require processing a large amount of training and testing model parameters and hyper-parameters, with high time-consuming. This approach seeks rapid damage detection in arch dams under dynamic conditions, to prevent potential disasters, by utilizing the RBF-NNN to seamlessly integrate the dynamic elastic modulus (DEM) and modal parameters (such as natural frequency and mode shape) as damage indicators. To determine the dynamic characteristics of the arch dam, the JA sequentially optimizes an objective function rooted in vibration-based data sets. Two case studies of hyperbolic concrete arch dams were carefully designed using finite element simulation to demonstrate the effectiveness of the RBF-NN model, in conjunction with the Jaya algorithm. The testing results demonstrated that the proposed methods could exhibit significant computational time-savings, while effectively detecting damage in arch dam structures with complex nonlinearities. Furthermore, despite training data contaminated with a high level of noise, the RBF-NN and JA fusion remained the robustness, with high accuracy.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.20 no.1
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• pp.56-65
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• 2024

Cast austenitic stainless steels (CASS) and austenitic stainless steel weldments with a ferrite-austenite duplex structure are widely used in nuclear power plants, incorporating ferrite phase to enhance strength, stress relief, and corrosion resistance. Thermal aging at 290-325℃ can induce embrittlement, primarily due to spinodal decomposition and G-phase precipitation in the ferrite phase. This study evaluates the effects of thermal aging by collecting and analyzing various mechanical properties, such as Charpy impact energy, ferrite microhardness, and tensile strength, from various literature sources. Different model expressions, including hyperbolic tangent and phase transformation equations, are applied to calculate activation energy (Q) of room-temperature impact energies, and the results are compared. Additionally, predictive models for Q based on material composition are evaluated, and the potential of machine learning techniques for improving prediction accuracy is explored. The study also examines the use of ferrite microhardness and tensile strength in calculating Q and assessing thermal embrittlement. The findings provide insights for developing advanced prediction models for the thermal embrittlement behavior of CASS and the weldments of austenitic steels, contributing to the safety and reliability of nuclear power plant components.

• Structural Engineering and Mechanics
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• v.90 no.1
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• pp.83-96
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• 2024

This paper suggests an analytical approach to investigate the free vibration and stability of functionally graded (FG) beams with both perfect and imperfect characteristics using a quasi-3D higher-order shear deformation theory (HSDT) with stretching effect. The study specifically focuses on FG beams resting on variable elastic foundations. In contrast to other shear deformation theories, this particular theory employs only four unknown functions instead of five. Moreover, this theory satisfies the boundary conditions of zero tension on the beam surfaces and facilitates hyperbolic distributions of transverse shear stresses without the necessity of shear correction factors. The elastic medium in consideration assumes the presence of two parameters, specifically Winkler-Pasternak foundations. The Winkler parameter exhibits variable variations in the longitudinal direction, including linear, parabolic, sinusoidal, cosine, exponential, and uniform, while the Pasternak parameter remains constant. The effective material characteristics of the functionally graded (FG) beam are assumed to follow a straightforward power-law distribution along the thickness direction. Additionally, the investigation of porosity includes the consideration of four different types of porosity distribution patterns, allowing for a comprehensive examination of its influence on the behavior of the beam. Using the virtual work principle, equations of motion are derived and solved analytically using Navier's method for simply supported FG beams. The accuracy is verified through comparisons with literature results. Parametric studies explore the impact of different parameters on free vibration and buckling behavior, demonstrating the theory's correctness and simplicity.

• Structural Engineering and Mechanics
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• v.89 no.3
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• pp.225-238
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• 2024

In this paper, a quasi-3D hyperbolic shear deformation theory for the bending responses of a functionally graded (FG) porous micro-beam is based on a modified couple stress theory requiring only one material length scale parameter that can capture the size influence. The model proposed accounts for both shear and normal deformation effects through an illustrative variation of all displacements across the thickness and satisfies the zero traction boundary conditions on the top and bottom surfaces of the micro-beam. The effective material properties of the functionally graded micro-beam are assumed to vary in the thickness direction and are estimated using the homogenization method of power law distribution, which is modified to approximate the porous material properties with even and uneven distributions of porosity phases. The equilibrium equations are obtained using the virtual work principle and solved using Navier's technique. The validity of the derived formulation is established by comparing it with the ones available in the literature. Numerical examples are presented to investigate the influences of the power law index, material length scale parameter, beam thickness, and shear and normal deformation effects on the mechanical characteristics of the FG micro-beam. The results demonstrate that the inclusion of the size effects increases the microbeams stiffness, which consequently leads to a reduction in deflections. In contrast, the shear and normal deformation effects are just the opposite.

• Structural Engineering and Mechanics
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• v.91 no.1
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• pp.1-23
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• 2024

This paper formulates a new integral shear deformation shell theory to investigate the free vibration response of carbon nanotube (CNT) reinforced structures with only four independent variables, unlike existing shell theories, which invariably and implicitly induce a host of unknowns. This approach guarantees traction-free boundary conditions without shear correction factors, using a non-polynomial hyperbolic warping function for transverse shear deformation and stress. By introducing undetermined integral terms, it will be possible to derive the motion equations with a low order of differentiation, which can facilitate a closed-form solution in conjunction with Navier's procedure. The mechanical properties of the CNT reinforcements are modeled to vary smoothly and gradually through the thickness coordinate, exhibiting different distribution patterns. A comparison study is performed to prove the efficacy of the formulated shell theory via obtained results from existing literature. Further numerical investigations are current and comprehensive in detailing the effects of CNT distribution patterns, volume fractions, and geometrical configurations on the fundamental frequencies of CNT-reinforced nanocomposite shells present here. The current shell theory is assumed to serve as a potent conceptual framework for designing reinforced structures and assessing their mechanical behavior.

• Journal of the Korean Geotechnical Society
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• v.21 no.2
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• pp.113-120
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• 2005

An understanding of soil-structure interaction is the key to rational and economical design for laterally loaded drilled shafts. It is very difficult to formulate the ultimate lateral capacity into a general equation because of the inherent soil nonlincarity, nonhomogeneity, and complexity enhanced by the three dimensional and asymmetric nature of the problem though extensive research works on the behavior of deep foundations subjected to lateral loads have been conducted for several decades. This study reviews the four most well known methods (i.e., Reese, Broms, Hansen, and Davidson) among many design methods according to the specific site conditions, the drilled shaft geometric characteristics (D/B ratios), and the loading conditions. And the hyperbolic lateral capacities (H$_h$) interpreted by the hyperbolic transformation of the load-displacement curves obtained from model tests carried out as a part of this research have been compared with the ultimate lateral capacities (Hu) predicted by the four methods. The H$_u$ / H$_h$ ratios from Reese's and Hansen's methods are 0.966 and 1.015, respectively, which shows both the two methods yield results very close to the test results. Whereas the H$_u$ predicted by Davidson's method is larger than H$_h$ by about $30\%$, the C.0.V. of the predicted lateral capacities by Davidson is the smallest among the four. Broms' method, the simplest among the few methods, gives H$_u$ / H$_h$ : 0.896, which estimates the ultimate lateral capacity smaller than the others because some other resisting sources against lateral loading are neglected in this method. But it results in one of the most reliable methods with the smallest S.D. in predicting the ultimate lateral capacity. Conclusively, none of the four can be superior to the others in a sense of the accuracy of predicting the ultimate lateral capacity. Also, regardless of how sophisticated or complicated the calculating procedures are, the reliability in the lateral capacity predictions seems to be a different issue.

• Korean Journal of Microbiology
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• v.52 no.3
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• pp.278-285
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• 2016

The bifunctional PheA protein, having chorismate mutase and prephenate dehydratase (CMPD) activities, is one of the key regulatory enzymes in the aromatic amino acid biosynthesis in Escherichia coli, and is negatively regulated by an end-product, phenyalanine. Therefore, PheA protein has been thought as useful for protein engineering to utilize mass production of essential amino acid phenylalanine. To obtain feedback resistant PheA protein against phenylalanine, we mutated by using random mutagenesis, extensively screened, and obtained $pheA^{FBR}$ gene encoding a feedback resistant PheA protein. The mutant PheA protein contains substitution of Leu to Phe at the position of 118, displaying that higher affinity (about $290{\mu}M$) for prephenate in comparison with that (about $850{\mu}M$) of wild type PheA protein. Kinetic analysis showed that the saturation curve of $PheA^{FBR}$ against phenyalanine is hyperbolic rather than that of $PheA^{WT}$, which is sigmoidal, indicating that the L118F mutant enzyme has no cooperative effects in prephenate binding in the presence of phenylalanine. In vitro enzymatic assay showed that the mutant protein exhibited increased activity by above 3.5 folds compared to the wild type enzyme. Moreover, L118F mutant protein appeared insensitive to feedback inhibition with keeping 40% of enzymatic activity even in the presence of 10 mM phenylalanine at which the activity of wild type $PheA^{WT}$ was not observed. The substitution of Leu to Phe in CMPD may induce significant conformational change for this enzyme to acquire feedback resistance to end-product of the pathway by modulating kinetic properties.

• Journal of Korean Society of Disaster and Security
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• v.12 no.2
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• pp.73-82
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• 2019

Recently, as the occurrence frequency of sudden floods due to climate change increased, the flood damage on riverside social infrastructures was extended so that there has been a threat of overflow. Therefore, a rapid prediction of potential flooding in riverside social infrastructure is necessary for administrators. However, most current flood forecasting models including hydraulic model have limitations which are the high accuracy of numerical results but longer simulation time. To alleviate such limitation, data driven models using artificial neural network have been widely used. However, there is a limitation that the existing models can not consider the time-series parameters. In this study the water surface elevation of the Hangang River bridge was predicted using the NARX model considering the time-series parameter. And the results of the ANN and RNN models are compared with the NARX model to determine the suitability of NARX model. Using the 10-year hydrological data from 2009 to 2018, 70% of the hydrological data were used for learning and 15% was used for testing and evaluation respectively. As a result of predicting the water surface elevation after 3 hours from the Hangang River bridge in 2018, the ANN, RNN and NARX models for RMSE were 0.20 m, 0.11 m, and 0.09 m, respectively, and 0.12 m, 0.06 m, and 0.05 m for MAE, and 1.56 m, 0.55 m and 0.10 m for peak errors respectively. By analyzing the error of the prediction results considering the time-series parameters, the NARX model is most suitable for predicting water surface elevation. This is because the NARX model can learn the trend of the time series data and also can derive the accurate prediction value even in the high water surface elevation prediction by using the hyperbolic tangent and Rectified Linear Unit function as an activation function. However, the NARX model has a limit to generate a vanishing gradient as the sequence length becomes longer. In the future, the accuracy of the water surface elevation prediction will be examined by using the LSTM model.

• Proceedings of the Korean Geotechical Society Conference
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• 1991.10a
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• pp.332-347
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• 1991

Accurate prediction of future settlement is essential for the settlement control of soft soil by pre-loading method. To predict future settlement in clayey soft soils, several methods like Asaoka method, Hyperbolic Method and Hoshino method are currently being used. These methods predict the future sett1ement by mathmatical treatment of the measured settlement data on the basis of consolidtion theory and empiricism. But the correlation coefficient between the measured and the predicted settlement was relatively low (0.8~0.9). Also, the prediction of future settlemet for the design load is very difficult. In this article, the measured field settlement data was treated as the the field consolidation test. Hence, condolidation coefficient(Cv) and compression index(Cc) was evaluated from the field settlement data. Cv and Cc values from field data was used to calculate the degree of consolidation and settlement at desired time. By this method, the correlation coefficent between the measured and the predicted settlement was significantly increased(0.97~0.99). Also the settlement by the design load after the improvement of soft soil could be predicted reasonably. This method is quite rational and sound but it requires thousands of calculation steps. Today, by the aid of low priced personal computers above mentioned technique could be used much acre economically and effectively than conventional methods. This article presented the mechanisms and capacities of this method and demonstrated the enhanced correlation coefficient when applied to actual field settlement data.