• Elastomers and Composites
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• v.43 no.1
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• pp.25-30
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• 2008

A bushing is a device used in automotive suspension systems to reduce the load transmitted from the wheel to the frame of the vehicle. A bushing is a hollow cylinder, which is bonded to a solid steel shaft at its inner surface and a steel sleeve at its outer surface. The relation between the force and moment applied to the shaft and the relative deformation and rotational angle of a bushing exhibits features of viscoelasticity. Since a moment-rotational angle relation for a bushing is important for multibody dynamics numerical simulations, the simple relation between the moment and rotational angle has been derived from experiment. It is shown that the predictions by the proposed moment-rotational angle relation are in very good agreement with the experimental results.

• Computers and Concrete
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• v.21 no.6
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• pp.717-726
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• 2018

Concrete pipelines are the most efficient and safe means for gas and oil transportation over a long distance. The use of nano materials and nono-engineering can be considered for enhancing concrete pipelines properties. the tests show that $SiO_2$ nanoparticles can improve the mechanical behavior of concrete. Moreover, severe hazard for pipelines is seismic ground motion. Over the years, scientists have attempted to understand pipe behavior against earthquake most frequently via numerical modeling and simulation. Therefore, in this paper, the dynamic response of underwater nanocomposite submerged pipeline conveying fluid is studied. The structure is subjected to the dynamic loads caused by earthquake and the governing equations of the system are derived using mathematical model via Classic shell theory and Hamilton's principle. Navier-Stokes equation is employed to calculate the force due to the fluid in the pipe. As well, the effect of external fluid is modeled with an external force. Mori-Tanaka approach is used to estimate the equivalent material properties of the nanocomposite. 1978 Tabas earthquake in Iran is considered for modelling seismic load. The dynamic displacement of the structure is extracted using differential quadrature method (DQM) and Newmark method. The effects of different parameters such as $SiO_2$ nanoparticles volume percent, boundary conditions, thickness to radius ratios, length to radius ratios, internal and external fluid pressure and earthquake intensity are discussed on the seismic response of the structure. From results obtained in this paper, it can be found that the dynamic response of the pipe is increased in the presence of internal and external fluid. Furthermore, the use of $SiO_2$ nanoparticles in concrete pipeline reduces the displacement of the structure during an earthquake.

• Journal of Soil and Groundwater Environment
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• v.26 no.6
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• pp.47-64
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• 2021

In this study, the annual and monthly groundwater recharge for the Sapgyo-cheon upstream basin in Chungnam Province was evaluated by water balance analysis utilizing WetSpass-M model. The modeling input data such as topography, climate parameters, LAI (Leaf Area Index), land use, and soil characteristics were established using ArcGIS, QGIS, and Python programs. The results showed that the annual average groundwater recharge in 2001 - 2020 was 251 mm, while the monthly groundwater recharge significantly varied over time, fluctuating between 1 and 47 mm. The variation was high in summer, and relatively low in winter. Variation in groundwater recharge was the largest in July in which precipitation was heavily concentrated, and the variation was closely associated with several factors including the total amount of precipitation, the number of days of the precipitation, and the daily average precipitation. This suggests the extent of groundwater recharge is greatly influenced not only by quantity of precipitation but also the precipitation pattern. Since climate condition has a profound effect on the monthly groundwater recharge, evaluation of monthly groundwater recharge need to be carried out by considering both seasonal and regional variability for better groundwater usage and management. In addition, the mathematical tools for groundwater recharge analysis need to be improved for more accurate prediction of groundwater recharge.

• Genomics & Informatics
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• v.19 no.1
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• pp.11.1-11.8
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• 2021

For the novel coronavirus disease 2019 (COVID-19), predictive modeling, in the literature, uses broadly susceptible exposed infected recoverd (SEIR)/SIR, agent-based, curve-fitting models. Governments and legislative bodies rely on insights from prediction models to suggest new policies and to assess the effectiveness of enforced policies. Therefore, access to accurate outbreak prediction models is essential to obtain insights into the likely spread and consequences of infectious diseases. The objective of this study is to predict the future COVID-19 situation of Korea. Here, we employed 5 models for this analysis; SEIR, local linear regression (LLR), negative binomial (NB) regression, segment Poisson, deep-learning based long short-term memory models (LSTM) and tree based gradient boosting machine (GBM). After prediction, model performance comparison was evelauated using relative mean squared errors (RMSE) for two sets of train (January 20, 2020-December 31, 2020 and January 20, 2020-January 31, 2021) and testing data (January 1, 2021-February 28, 2021 and February 1, 2021-February 28, 2021) . Except for segmented Poisson model, the other models predicted a decline in the daily confirmed cases in the country for the coming future. RMSE values' comparison showed that LLR, GBM, SEIR, NB, and LSTM respectively, performed well in the forecasting of the pandemic situation of the country. A good understanding of the epidemic dynamics would greatly enhance the control and prevention of COVID-19 and other infectious diseases. Therefore, with increasing daily confirmed cases since this year, these results could help in the pandemic response by informing decisions about planning, resource allocation, and decision concerning social distancing policies.

• Steel and Composite Structures
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• v.30 no.3
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• pp.281-292
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• 2019

In this paper, analysis of critical fluid velocity and heat transfer in the nanocomposite pipes conveying nanofluid is presented. The pipe is reinforced by carbon nanotubes (CNTs) and the fluid is mixed by $AL_2O_3$ nanoparticles. The material properties of the nanocomposite pipe and nanofluid are considered temperature-dependent and the structure is subjected to magnetic field. The forces of fluid viscosity and turbulent pressure are obtained using momentum equations of fluid. Based on energy balance, the convection of inner and outer fluids, conduction of pipe and heat generation are considered. For mathematical modeling of the nanocomposite pipes, the first order shear deformation theory (FSDT) and energy method are used. Utilizing the Lagrange method, the coupled pipe-nanofluid motion equations are derived. Applying a semi-analytical method, the motion equations are solved for obtaining the critical fluid velocity and critical Reynolds and Nusselt numbers. The effects of CNTs volume percent, $AL_2O_3$ nanoparticles volume percent, length to radius ratio of the pipe and shell surface roughness were shown on the critical fluid velocity, critical Reynolds and Nusselt numbers. The results are validated with other published work which shows the accuracy of obtained results of this work. Numerical results indicate that for heat generation of $Q=10MW/m^3$, adding 6% $AL_2O_3$ nanoparticles to the fluid increases 20% the critical fluid velocity and 15% the Nusselt number which can be useful for heat exchangers.

• Journal of Environmental Health Sciences
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• v.44 no.6
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• pp.524-538
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• 2018

Objective: This study aimed to identify the size distributions of particulate matter emitted during 3D printing according to operational conditions and estimate particle inhalation exposure doses at each respiratory region. Methods: Four types of printing filaments were selected: acrylonitrile-butadiene-styrene (ABS), polylactic acid (PLA), Laywood, and nylon. A fused deposition modeling (FDM) 3D printer was used for printing. Airborne particles between 10 nm and $10{\mu}m$ were measured before, during, and after printing using real-time monitors under extruder temperatures from 215 to $290^{\circ}C$. Inhalation exposures, including inhaled and deposited doses at the respiratory regions, were estimated using a mathematical model. Results: Nanoparticles dominated among the particles emitted during printing, and more particles were emitted with higher temperatures for all materials. Under all temperature conditions, the Laywood emitted the highest particle concentration, followed by ABS, PLA, and nylon. The particle concentration peaked for the initial 10 to 20 minutes after starting operations and gradually decreased with elapsed time. Nanoparticles accounted for a large proportion of the total inhaled particles in terms of number, and about a half of the inhaled nanoparticles were estimated to be deposited in the alveolar region. In the case of the mass of inhaled and deposited dose, particles between 0.1 and $1.0{\mu}m$ made up a large proportion. Conclusion: The number of consumers using 3D printers is expected to expand, but hazardous emissions such as thermal byproducts from 3D printing are still unclear. Further studies should be conducted and appropriate control strategies considered in order to minimize human exposure.

• Journal of the Korea Convergence Society
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• v.10 no.1
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• pp.7-12
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• 2019

The application of neural networks to stock forecasting has received a great deal of attention because no assumption about a suitable mathematical model has to be made prior to forecasting and they are capable of extracting useful information from data, which is required to describe nonlinear input-output relations of stock forecasting. The paper builds neural network models to forecast daily KOrea composite Stock Price Index (KOSPI), and their performance is demonstrated. MAPEs of NN1 model show 0.427 and 0.627 in its learning and test, respectively. Based on the predicted KOSPI price, the paper proposes an alpha trading for trades in Exchange Traded Funds (ETFs) that fluctuate with the KOSPI200. The alpha trading is tested with data from 125 trade days, and its trade return of 7.16 ~ 15.29 % suggests that the proposed alpha trading is effective.

• Computers and Concrete
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• v.24 no.2
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• pp.125-135
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• 2019

Concrete pipelines are the most efficient and safe means for gas and oil transportation over a long distance. The use of nano materials and nono-engineering can be considered for enhancing concrete pipelines properties. the tests show that SiO2 nanoparticles can improve the mechanical behavior of concrete. Moreover, severe hazard for pipelines is seismic ground motion. Over the years, scientists have attempted to understand pipe behavior against earthquake most frequently via numerical modeling and simulation. Therefore, in this paper, the dynamic response of underwater nanocomposite submerged pipeline conveying fluid is studied. The structure is subjected to the dynamic loads caused by earthquake and the governing equations of the system are derived using mathematical model via Classic shell theory and Hamilton's principle. Navier-Stokes equation is employed to calculate the force due to the fluid in the pipe. As well, the effect of external fluid is modeled with an external force. Mori-Tanaka approach is used to estimate the equivalent material properties of the nanocomposite. 1978 Tabas earthquake in Iran is considered for modelling seismic load. The dynamic displacement of the structure is extracted using differential quadrature method (DQM) and Newmark method. The effects of different parameters such as SiO2 nanoparticles volume percent, boundary conditions, thickness to radius ratios, length to radius ratios, internal and external fluid pressure and earthquake intensity are discussed on the seismic response of the structure. From results obtained in this paper, it can be found that the dynamic response of the pipe is increased in the presence of internal and external fluid. Furthermore, the use of SiO2 nanoparticles in concrete pipeline reduces the displacement of the structure during an earthquake.

• Journal of Aerospace System Engineering
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• v.13 no.2
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• pp.51-59
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• 2019

Subsequently, Part I [1], which was about the single-cell model, a composite thin-walled beam with a multi-cell of chord-wise asymmetric cross-section, was selected in this study. Moreover, the theoretical dynamic characteristics of the model were analyzed. For this analysis, mathematical modeling was performed by considering the warping restraint effects, transverse shear effects, taper ratio and cross-section ratio. Similar to part I, the mass, stiffness coefficients and Eigen frequencies of the multi-cell section considered were investigated. In particular, the comparison between the multi-cell and single-cell sections and the effects of the cross-section ratio and taper ratio of the model on the Eigen frequencies were analyzed. However, the results compared when the asymmetry of the section was considered and warping function were not corrected.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.9
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• pp.749-757
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• 2021

In transportation missions using quadrotor, the payload may change the model parameters, such as mass, moment of inertia, and center of gravity. Moreover, if position of the payload is constantly changing during flight, the effect can adversely affect the control performances. To handle this issue, we suggest Model Reference Adaptive Control based on Linear Quadratic Regulator(LQR+MRAC) to compensate the uncertainty caused by payload. Firstly, the mathematical modeling with the fixed payload is derived. Second, Linear Quadratic Regulator (LQR) is used to design the reference model and baseline controller. Also, through the Stability method, Adaptive law is derived to estimate the model parameters. To verify the performance of proposed control scheme, we compared LQR and LQR+MRAC in situations where uncertainties exist. And, when the disturbance exist, the classic MRAC and proposed controller is compared to analyze the transient response and robustness.