• Geomechanics and Engineering
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• v.13 no.4
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• pp.601-619
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• 2017

Cantilever retaining wall movements generally depend on the intensity and duration of ground motion, the response of the soil underlying the wall, the response of the backfill, the structural rigidity, and soil-structure interaction (SSI). This paper investigates the effect of material properties on seismic response of backfill-cantilever retaining wall-soil/foundation interaction system considering SSI. The material properties varied include the modulus of elasticity, Poisson's ratio, and mass density of the wall material. A series of nonlinear time history analyses with variation of material properties of the cantilever retaining wall are carried out by using the suggested finite element model (FEM). The backfill and foundation soil are modelled as an elastoplastic medium obeying the Drucker-Prager yield criterion, and the backfill-wall interface behavior is taken into consideration by using interface elements between the wall and soil to allow for de-bonding. The viscous boundary model is used in three dimensions to consider radiational effect of the seismic waves through the soil medium. In the seismic analyses, North-South component of the ground motion recorded during August 17, 1999 Kocaeli Earthquake in Yarimca station is used. Dynamic equations of motions are solved by using Newmark's direct step-by-step integration method. The response quantities incorporate the lateral displacements of the wall relative to the moving base and the stresses in the wall in all directions. The results show that while the modulus of elasticity has a considerable effect on seismic behavior of cantilever retaining wall, the Poisson's ratio and mass density of the wall material have negligible effects on seismic response.

• Structural Engineering and Mechanics
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• v.74 no.6
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• pp.809-819
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• 2020

For the first time, the influence of in-plane magnetic field on wave propagation of Graphene Nano-Platelets (GNPs) polymer composite nanoplates is investigated here. The impact of three- parameter Kerr foundation is also considered. There are two different reinforcement distribution patterns (i.e. uniformly and non-uniformly) while the material properties of the nanoplate are estimated through the Halpin-Tsai model and a rule of mixture. To consider the size-dependent behavior of the structure, Eringen Nonlocal Differential Model (ENDM) is utilized. The equations of wave motion derived based on a higher-order shear deformation refined theory through Hamilton's principle and an analytical technique depending on Taylor series utilized to find the wave frequency as well as phase velocity of the GNPs reinforced nanoplates. A parametric investigation is performed to determine the influence of essential phenomena, such as the nonlocality, GNPs conditions, Kerr foundation parameters, and wave number on the both longitudinal and flexural wave characteristics of GNPs reinforced nanoplates.

• Journal of the Korean Magnetic Resonance Society
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• v.19 no.1
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• pp.1-10
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• 2015

Refinements with atomistic molecular dynamics (MD) simulation have contributed to improving the qualities of NMR structures. In most cases, the calculations with atomistic MD simulation for NMR structures employ generalized-Born implicit solvent model (GBIS) to take into accounts solvation effects. Developments in algorithms and computational capacities have ameliorated GBIS to approximate solvation effects that explicit solvents bring about. However, the quantitative comparison of NMR structures in the latest GBIS and explicit solvents is lacking. In this study, we report the direct comparison of NMR structures that atomistic MD simulation coupled with GBIS and water molecules refined. Two model proteins, GB1 and ubiquitin, were recalculated with experimental distance and torsion angle restraints, under a series of simulated annealing time steps. Whereas the root mean square deviations of the resulting structures were apparently similar, AMBER energies, the most favored regions in Ramachandran plot, and MolProbity clash scores witnessed that GBIS-refined structures had the better geometries. The outperformance by GBIS was distinct in the structure calculations with sparse experimental restraints. We show that the superiority stemmed, at least in parts, from the inclusion of all the pairs of non-bonded interactions. The shorter computational times with GBIS than those for explicit solvents makes GBIS a powerful method for improving structural qualities particularly under the conditions that experimental restraints are insufficient. We also propose a method to separate the native-like folds from non-violating diverged structures.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.7
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• pp.1-9
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• 2021

This paper investigates the impact of the domestic and global outbreak of the coronavirus (COVID-19) pandemic on the trading size of the Malaysian stock (MS) market. The theoretical model posits that stock markets are affected by their response to disasters and events that arise in the international or local environments, as well as to several financial factors such as stock volatility and spread bid-ask prices. Using daily time-series data from 27 January to 12 May 2020, this paper utilizes the traditional Augmented Dickey and Fuller (ADF) technique and Zivot and Andrews with structural break' procedures for a stationarity test analysis, while the autoregressive distributed lag (ARDL) method is applied according to the trading size of the MS market model. The analysis considered almost all 789 listed companies investing in the main stock market of Malaysia. The results confirmed our hypotheses that both the daily growth in the active domestic and global cases of coronavirus (COVID-19) has significant negative effects on the daily trading size of the stock market in Malaysia. Although the COVID-19 has a negative effect on the Malaysian stock market, the findings of this study suggest that the COVID-19 pandemic may have an asymmetric effect on the market.

• Korean Journal of Agricultural Science
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• v.49 no.1
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• pp.61-75
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• 2022

The first purpose of this study is to evaluate the usefulness of pork traceability data, which is monthly time-series data, and to draw implications with regard to its usefulness. The second purpose is to construct a dynamic ecological equation model (DEEM) that reflects the biological characteristics at each growth stage, such as pregnancy, birth and growth, and the slaughter of pigs, using traceability data. With the monthly pig model devised in this study, it is expected that the number of slaughtered animals (supply) that can be shipped in the future is predictable and that policy simulations are possible. However, this study was limited to traceability data and focused only on building a supply-side model. As a result of verifying the traceability data, it was found that approximately 6% of farms produce by mixing great grand parent (GGP), grand parent (GP), parent stock (PS), and artificial insemination (AI), meaning that it is necessary to separate them by business type. However, the analysis also showed that the coefficient values estimated by constructing an equation for each growth stage were consistent with the pig growth outcomes. Also, the model predictive power test was excellent. For this reason, it is judged that the model design and traceability data constructed with the cohort and the dynamic ecological equation model system considering biological growth and shipment times are excellent. Finally, the model constructed in this study is expected to be used as basic data to inform producers in their decision-making activities and to help with governmental policy directions with regard to supply and demand. Research on the demand side is left for future researchers.

• Korean Journal of Organic Agriculture
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• v.18 no.3
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• pp.315-329
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• 2010

This study focused on analysis of the satisfaction level of specialty shops for environment-friendly agricultural products (EFAP). To analyze the satisfaction level of EF AP, a series of household surveys were conducted. Questionnaire was prepared on the basis of the SERVQUAL model and the structural equation modeling was made on the basis of the contents surveyed. The main results of this study are summarized as follows. Firstly, tangibles structured with store clearance, neat uniform, information and others is the factor of service quality satisfaction. Secondly, reliability structured with service practice, problem solving, and service in accurate time is the factor of service quality satisfaction. Thirdly, assurance structured with the reliability of employees, sufficient knowledge of employees, courteous and good manner is the factor of service quality satisfaction. Fourthly, responsiveness structured with prompt service, voluntary help, customer response service and the like is the factor of service quality satisfaction. Fifthly, the sympathy structured in interest for each customer, provision of service in time convenient to use, encountering the customers with genuine feeling are the factors of service quality satisfaction. And sixthly, the service satisfaction factors would influence on the consumer behavior factors.

• Structural Monitoring and Maintenance
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• v.4 no.2
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• pp.115-131
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• 2017

Classical flutter of wind turbine blades indicates a type of aeroelastic instability with fully attached boundary layer where a torsional blade mode couples to a flapwise bending mode, resulting in a mutual rapid growth of the amplitudes. In this paper the monitoring problem of onset of flutter is investigated from a detection point of view. The criterion is stated in terms of the exceeding of a defined envelope process of a specific maximum torsional vibration threshold. At a certain instant of time, a limited part of the previously measured torsional vibration signal at the tip of blade is decomposed through the Empirical Mode Decomposition (EMD) method, and the 1st Intrinsic Mode Function (IMF) is assumed to represent the response in the flutter mode. Next, an envelope time series of the indicated modal response is obtained in terms of a Hilbert transform. Finally, a flutter onset criterion is proposed, based on the indicated envelope process. The proposed online flutter monitoring method provided a practical and direct way to detect onset of flutter during operation. The algorithm has been illustrated by a 907-DOFs aeroelastic model for wind turbines, where the tower and the drive train is modelled by 7 DOFs, and each blade by means of 50 3-D Bernoulli-Euler beam elements.

• Smart Structures and Systems
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• v.21 no.2
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• pp.171-185
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• 2018

Maintenance of deteriorated bridge structures has always been one of the challenging issues in developing countries as it is directly related to daily life of people including trade and economy. An effective maintenance strategy is highly dependent on timely inspections on the bridge health condition. This study is intended to investigate an approach for detecting bridge damage for the long-term health monitoring by use of copula theory. Long-term measured data for the seven-span plate-Gerber bridge is investigated. Autoregressive time series models constructed for the observed accelerations taken from the bridge are utilized for the computation of damage indicator for the bridge. The copula model is used to analyze the statistical changes associated with the modal parameters. The changes in the modal parameters with the time are identified by the copula statistical properties. Applicability of the proposed method is also discussed based on a comparison study among other approaches.

• Structural Engineering and Mechanics
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• v.77 no.1
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• pp.1-17
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• 2021

The influence of prestress force on the fundamental frequency and static deflection shape of uncracked Prestressed Concrete (PC) beams with a parabolic bonded tendon was examined in this paper. Due to the conflicts among existing theories, the analytical solutions for properly considering the dynamic and static behavior of these members is not straightforward. A series of experiments were conducted for a total period of approximately 2.5 months on a PC beam made with high strength concrete, subsequently and closely to the 28 days of age of concrete. Specifically, the simply supported PC member was short term subjected to free transverse vibration and three-point bending tests during its early-age. Subsequently, the experimental data were compared with a model that describes the dynamic behavior of PC girders as a combination of two substructures interconnected, i.e., a compressed Euler-Bernoulli beam and a tensioned parabolic cable. It was established that the fundamental frequency of uncracked PC beams with a parabolic bonded tendon is sensitive to the variation of the initial elastic modulus of concrete in the early-age curing. Furthermore, the small variation in experimental frequency with time makes doubtful its use in inverse problem identifications. Conversely, the relationship between prestress force and static deflection shape is well described by the magnification factor formula of the "compression-softening" theory by assuming the variation of the chord elastic modulus of concrete with time.

• Smart Structures and Systems
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• v.29 no.1
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• pp.17-28
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• 2022

The cable component of cable-stayed bridges is gradually impacted by weather conditions, vehicle loads, and material corrosion. The stayed cable is a critical load-carrying part that closely affects the operational stability of a cable-stayed bridge. Damaged cables might lead to the bridge collapse due to their tension capacity reduction. Thus, it is necessary to develop structural health monitoring (SHM) techniques that accurately identify damaged cables. In this work, a combinational identification method of three efficient techniques, including statistical analysis, clustering, and neural network models, is proposed to detect the damaged cable in a cable-stayed bridge. The measured dataset from the bridge was initially preprocessed to remove the outlier channels. Then, the theory and application of each technique for damage detection were introduced. In general, the statistical approach extracts the parameters representing the damage within time series, and the clustering approach identifies the outliers from the data signals as damaged members, while the deep learning approach uses the nonlinear data dependencies in SHM for the training model. The performance of these approaches in classifying the damaged cable was assessed, and the combinational identification method was obtained using the voting ensemble. Finally, the combination method was compared with an existing outlier detection algorithm, support vector machines (SVM). The results demonstrate that the proposed method is robust and provides higher accuracy for the damaged cable detection in the cable-stayed bridge.