• The Korean Journal of Applied Statistics
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• v.34 no.4
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• pp.659-669
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• 2021

Multivariate regression often appears in longitudinal or functional data analysis. Since multivariate regression involves multi-dimensional response variables, it is more strongly affected by the so-called curse of dimension that univariate regression. To overcome this issue, Yoo (2018) and Yoo (2019a) proposed three model-based response dimension reduction methodologies. According to various numerical studies in Yoo (2019a), the default method suggested in Yoo (2019a) is least sensitive to the simulated models, but it is not the best one. To release this issue, the paper proposes an selection algorithm by comparing the other two methods with the default one. This approach is called principal selected response reduction. Various simulation studies show that the proposed method provides more accurate estimation results than the default one by Yoo (2019a), and it confirms practical and empirical usefulness of the propose method over the default one by Yoo (2019a).

• Structural Engineering and Mechanics
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• v.78 no.2
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• pp.117-124
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• 2021

This work focused on the novel numerical tool for the bending responses of carbon nanotube reinforced composites (CNTRC) beams. The higher order shear deformation beam theory (HSDT) is used to determine strain-displacement relationships. A new exponential function was introduced into the carbon nanotube (CNT) volume fraction equation to show the effect of the CNT distribution on the CNTRC beams through displacements and stresses. To determine the mechanical properties of CNTRCs, the rule of the mixture was employed by assuming that the single-walled carbon nanotubes (SWCNTs)are aligned and distributed in the matrix. The governing equations were derived by Hamilton's principle, and the mathematical models presented in this work are numerically provided to verify the accuracy of the present theory. The effects of aspect ratio (l/d), CNT volume fraction (Vcnt), and the order of exponent (n) on the displacement and stresses are presented and discussed in detail. Based on the analytical results. It turns out that the increase of the exponent degree (n) makes the X-beam stiffer and the exponential CNTs distribution plays an indispensable role to improve the mechanical properties of the CNTRC beams.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.33 no.6
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• pp.401-409
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• 2020

Seismic fragility assessments include a procedure to combine the random variables of response and capacity to produce the relationship between failure probability and seismic intensity. The evaluation of the failure probability of simultaneous multiple failures of two or more components assumes that the failure probability of each component is independent of those of the others. However, a correlation is expected to exist because several random factors have the same cause. The multiple-failure probability can differ depending on this correlation and may be unconservative without considering the seismic correlation. Therefore, a practical methodology for fragility assessment should be evaluated using the seismic correlation and correlation coefficient for each random variable. In this study, several random variables were selected for numerical evaluation of the correlation coefficient. The correlation coefficient was then compared with each variable and the combined variables. The correlation coefficient using simplified and complex models were also compared to determine and analyze the differences between each of the approaches.

• International Journal of Naval Architecture and Ocean Engineering
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• v.12 no.1
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• pp.491-500
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• 2020

The present study proposes a time domain model for the Vortex-induced Vibration (VIV) simulation of a catenary riser under the combination of the current and oscillatory flow induced by vessel motion. In this model, the hydrodynamic force of VIV comprises excitation force, hydrodynamic damping and added mass, which are taken as functions of the non-dimensional frequency and amplitude ratio. The non-dimensional frequency is related with the response frequency, natural frequency, lock-in range and the fluid velocity. The relatively oscillatory flow induced by vessel motion is taken into account in the fluid velocity. Considering that the added mass coefficient and the non-dimensional frequency can affect each other, an iterative analysis is conducted at each time step to update the added mass coefficient and the natural frequency. This model is in detail validated against the published test models. The results show that the model can reasonably reflect the effect of the added mass coefficient on the VIV, and can well predict the riser's VIV under stationary and oscillatory flow induced by vessel motion. Based on the model, this study carries out the VIV simulation of a catenary riser with harmonic vessel motion. By analyzing the bending moment near the touchdown point, it is found that under the combination of the ocean current and oscillatory flow the vessel motion may decrease the VIV response, while increase the excited frequencies. In addition, the decreasing rate of the VIV under vessel surge is larger than that under vessel heave at small vessel motion velocity, while the situation becomes opposite at large vessel motion velocity.

• Journal of Korea Society of Industrial Information Systems
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• v.26 no.3
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• pp.9-22
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• 2021

This study proposes a supply chain network (SCN) model considering supply disruption in assembly industry. For supply disruption, supplier disruption and its route disruption are simultaneously taken into consideration in the SCN model. With the simultaneous consideration, the SCN model can achieve its flexibility and efficiency. A mathematical formulation is suggested for representing the SCN model, and a proposed hybrid genetic algorithm (pro-HGA) is used for implementing the mathematical formulation. In numerical experiment, the performance of the pro-HGA approach is compared with those of some conventional approaches using the SCN models with various scales, and a sensitivity analysis considering the change of the numbers of suppliers and backup routes is done. Experimental results show that the performances of the pro-HGA approach are superior to those of the conventional approaches, and the flexibility and efficiency of the SCN model considering supply disruption are proved. Finally, the significance of this study is summarized and a potential future research direction is mentioned in conclusion.

• Smart Structures and Systems
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• v.26 no.6
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• pp.693-701
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• 2020

The conventional Kalman Filter (KF) provides a promising way for structural state estimation. However, the physical parameters of structural systems or models should be available for the estimation. Moreover, it is not applicable when the loadings applied to the structures are unknown. To circumvent the aforementioned limitations, a two-stage KF with unknown input approach is proposed for the simultaneous identification of structural parameters and unknown loadings. In stage 1, a modified observation equation is employed. The structural state vector is estimated by KF on the basis of structural parameters identified at the previous time-step. Then, the unknown input is identified by Least Squares Estimation (LSE). In stage 2, based on the concept of sensitivity matrix, the structural parameters are updated at the current time-step by using the estimated structural states obtained from stage 1. The effectiveness of the proposed approach is numerically validated via a five-story shearing model under random and earthquake excitations. Shaking table tests on a five-story structure are also employed to demonstrate the performance of the proposed approach. It is demonstrated from numerical and experimental results that the proposed approach can be used for the identification of parameters of structure and the external force applied to it with acceptable accuracy.

• Steel and Composite Structures
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• v.39 no.5
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• pp.631-643
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• 2021

The aim of this work is to study the hygro-thermo-mechanical bending responses of simply supported FG plate resting on a Winkler-Pasternak elastic foundation. The effect transverse shear strains is taken into account in which the zero transverse shear stress condition on the top and bottom surfaces of the plate is ensured without using any shear correction factors. The developed model contains only four unknowns variable which is reduced compared to other HSDTs models. The material properties of FG-plate are supposed to vary across the thickness of the plate according to power-law mixture. The differential governing equations are derived based on the virtual working principle. Numerical outcomes of bending analysis of FG plates under hygro-thermo-mechanical loads are performed and compared with those available in the literature. The effects of the temperature, moisture concentration, elastic foundation parameters, shear deformation, geometrical parameters, and power-law-index on the dimensionless deflections, axial and transverse shear stresses of the FG-plate are presented and discussed.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.34 no.2
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• pp.71-75
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• 2021

Despite the development of computational resources, the need to analyze models is increasing. The size of model has been increased to analyze the entire structure more accurately and precisely. As the analysis model becomes larger and more complex, the computation time increases exponentially. Various industries use many structures that have repeated patterns. We focus on these structures with repeated patterns and propose a dynamic analysis method to efficiently calculate these repeated structures. To devise an efficient method for repeated structures, the substructuring scheme and the degree of freedom-based reduction method are used in this study. We modify the existing reduction method in consideration of the characteristics of the repeating structure. In the proposed method, the entire structure was expressed as a combination of substructures, where each substructure was represented as an unit cell of repeated structures. The substructures were condensed and assembled using the substructuring scheme and the modified condensation method. Finally, numerical examples were demonstrated to verify the efficiency and accuracy of proposed method.

• International Journal of Computer Science & Network Security
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• v.21 no.6
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• pp.47-53
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• 2021

The article deals with the problems of application of microwave methods in systems of geoecological monitoring of natural environments and resources of the agro-industrial complex. It is noted that the methods of microwave radiometry make it possible, by the power of the measured intrinsic radio-thermal radiation of the atmosphere, when solving inverse problems using empirical and semi-empirical models, to determine such parameters of the atmosphere as thermodynamic temperature, humidity, water content, moisture content, precipitation intensity, and the presence of different fractions of clouds.In addition to assessing the meteorological parameters of the atmosphere and the geophysical parameters of the underlying surface based on the data of microwave radiometric measurements, it is possible to promptly detect and study pollution of both the atmosphere and the earth's surface. A technique has been developed for the analysis of sources of measurement error and their numerical evaluation, because they have a significant effect on the accuracy of solving inverse problems of reconstructing the values of the physical parameters of the probed media.To analyze the degree of influence of the limited spatial selectivity of the antenna of the microwave radiometric system on the measurement error, we calculated the relative measurement error of the ratio of radio brightness contrasts in two angular directions. It has been determined that in the system of geoecological monitoring of natural environments, the effect of background noise is maximal with small changes in the radiobrightness temperature during angular scanning and high sensitivity of the receiving equipment.

• Advances in concrete construction
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• v.10 no.6
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• pp.479-488
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• 2020

The experimental and numerical works were carried out on high performance fiber reinforced concrete (HPFRC) with w/cm ratios ranging from 0.25 to 0.40, fiber volume fraction (Vf)=0-1.5% and 10% silica fume replacement. Improvements in compressive and flexural strengths obtained for HPFRC are moderate and significant, respectively, Empirical equations developed for the compressive strength and flexural strength of HPFRC as a function of fiber volume fraction. A relation between flexural strength and compressive strength of HPFRC with R=0.78 was developed. Due to the complex mix proportions and non-linear relationship between the mix proportions and properties, models with reliable predictive capabilities are not developed and also research on HPFRC was empirical. In this paper due to the inadequacy of present method, a back propagation-neural network (BP-NN) was employed to estimate the 28-day compressive strength of HPFRC mixes. BP-NN model was built to implement the highly non-linear relationship between the mix proportions and their properties. This paper describes the data sets collected, training of ANNs and comparison of the experimental results obtained for various mixtures. On statistical analyses of collected data, a multiple linear regression (MLR) model with R2=0.78 was developed for the prediction of compressive strength of HPFRC mixes, and average absolute error (AAE) obtained is 6.5%. On validation of the data sets by NNs, the error range was within 2% of the actual values. ANN model has given the significant degree of accuracy and reliability compared to the MLR model. ANN approach can be effectively used to estimate the 28-day compressive strength of fibrous concrete mixes and is practical.