• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.4
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• pp.431-437
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• 2019

PLC(Power Line Communication) is being used in various ways in smart grid system because of the advantages of low cost and high data throughput. However, power line channel has many problems due to impulse noise and various studies have been conducted to solve the problem. Recently, ACDL(Adaptive Cannonical Differential Limiter) which is based on an adaptive clipping with analog nonlinear filter, has been proposed and performs better than the others. In this paper, we show that ACDL is similar to the detection of slew rate with oversampled digital signal by simplification and analysis. Through the simulation under the PRIME standard it is shown that the proposed performs equal to or better than that of ACDL, but significantly reduce the complexity to implement. The BER performance is equal but the complexity is reduced to less than 10%.

• Journal of the Earthquake Engineering Society of Korea
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• v.23 no.3
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• pp.159-167
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• 2019

2016 Gyeongju and 2017 Pohang earthquakes led Koreans to acknowledge that the Korean peninsula is not an earthquake-free zone anymore. Among various buildings crucial to after-shock recovery, general hospital buildings, especially existing old ones, are very significant so seismic retrofitting of those must be an important issue. Self-centering energy dissipative(SCED) brace is one of retrofitting methods, which consists of tendon with restoring force and friction device capable of dissipating seismic energy. The strength of the SCED brace is that the tendon forces a structure to go back to the original position, which means residual drift can be negligible. The residual drift is a very important parameter to determine usableness of general hospitals after shock. To the contrary, buckling-restrained braces(BRB) are also a very effective way to retrofit because they can resist both compressive and tensile, but residual drift may exist when the steel core yields. On this background, the seismic retrofitting effect of general hospitals reinforced with SCED braces was investigated and compared to that of the BRD in this study. As a result, although the floor acceleration cannot be reduced, the story drift and residual drift, and the shear demand of walls significantly decreased. Consequently, seismic retrofitting by SCED braces are very effective for domestic low-rise general hospitals.

• Earthquakes and Structures
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• v.22 no.6
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• pp.539-548
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• 2022

Steel plate shear walls (SPSWs) are one of the most important and widely used lateral load-bearing systems. The reason for this is easier execution than reinforced concrete (RC) shear walls, faster construction time, and lower final weight of the structure. However, the main drawback of SPSWs is premature buckling in low drift ratios, which affects the energy absorption capacity and global performance of the system. To address this problem, two groups of SPSWs under cyclic loading were investigated using the finite element method (FEM). In the first group, several series of circular rings have been used and in the second group, a new type of SPSW with concentric circular rings (CCRs) has been introduced. Numerous parameters include in yield stress of steel plate wall materials, steel panel thickness, and ring width were considered in nonlinear static analysis. At first, a three-dimensional (3D) numerical model was validated using three sets of laboratory SPSWs and the difference in results between numerical models and experimental specimens was less than 5% in all cases. The results of numerical models revealed that the full SPSW undergoes shear buckling at a drift ratio of 0.2% and its hysteresis behavior has a pinching in the middle part of load-drift ratio curve. Whereas, in the two categories of proposed SPSWs, the hysteresis behavior is complete and stable, and in most cases no capacity degradation of up to 6% drift ratio has been observed. Also, in most numerical models, the tangential stiffness remains almost constant in each cycle. Finally, for the innovative SPSW, a relationship was suggested to determine the shear capacity of the proposed steel wall relative to the wall slenderness coefficient.

• Steel and Composite Structures
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• v.44 no.2
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• pp.241-254
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• 2022

The cables in a cable-stayed bridge are critical load-carrying parts. The potential damage to cables should be identified early to prevent disasters. In this study, an efficient deep learning model is proposed for the damage identification of cables using both a multi-layer perceptron (MLP) and a graph neural network (GNN). Datasets are first generated using the practical advanced analysis program (PAAP), which is a robust program for modeling and analyzing bridge structures with low computational costs. The model based on the MLP and GNN can capture complex nonlinear correlations between the vibration characteristics in the input data and the cable system damage in the output data. Multiple hidden layers with an activation function are used in the MLP to expand the original input vector of the limited measurement data to obtain a complete output data vector that preserves sufficient information for constructing the graph in the GNN. Using the gated recurrent unit and set2set model, the GNN maps the formed graph feature to the output cable damage through several updating times and provides the damage results to both the classification and regression outputs. The model is fine-tuned with the original input data using Adam optimization for the final objective function. A case study of an actual cable-stayed bridge was considered to evaluate the model performance. The results demonstrate that the proposed model provides high accuracy (over 90%) in classification and satisfactory correlation coefficients (over 0.98) in regression and is a robust approach to obtain effective identification results with a limited quantity of input data.

• Steel and Composite Structures
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• v.41 no.5
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• pp.761-773
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• 2021

This study presents a 3D non-linear finite element (FE) assessment of dynamic soil-structure interaction (SSI). The numerical investigation has been performed on the time domain through a Finite Element (FE) system, while considering the nonlinear behavior of soil and the multi-directional nature of genuine seismic events. Later, the FE outcomes are analyzed to the recorded in-situ free-field and structural movements, emphasizing the numerical model's great result in duplicating the observed response. In this work, the soil response is simulated using an isotropic hardening elastic-plastic hysteretic model utilizing HSsmall. It is feasible to define the non-linear cycle response from small to large strain amplitudes through this model as well as for the shift in beginning stiffness with depth that happens during cyclic loading. One of the most difficult and unexpected tasks in resolving soil-structure interaction concerns is picking an appropriate ground motion predicted across an earthquake or assessing the geometrical abnormalities in the soil waves. Furthermore, an artificial neural network (ANN) has been utilized to properly forecast the non-linear behavior of soil and its multi-directional character, which demonstrated the accuracy of the ANN based on the RMSE and R² values. The total result of this research demonstrates that complicated dynamic soil-structure interaction processes may be addressed directly by passing the significant simplifications of well-established substructure techniques.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.1
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• pp.23-31
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• 2023

Research and interest in sustainable printing are increasing in the packaging printing industry. Currently, predicting the amount of ink required for each work is based on the experience and intuition of field workers. Suppose the amount of ink produced is more than necessary. In this case, the rest of the ink cannot be reused and is discarded, adversely affecting the company's productivity and environment. Nowadays, machine learning models can be used to figure out this problem. This study compares the ink usage prediction machine learning models. A simple linear regression model, Multiple Regression Analysis, cannot reflect the nonlinear relationship between the variables required for packaging printing, so there is a limit to accurately predicting the amount of ink needed. This study has established various prediction models which are based on CART (Classification and Regression Tree), such as Decision Tree, Random Forest, Gradient Boosting Machine, and XGBoost. The accuracy of the models is determined by the K-fold cross-validation. Error metrics such as root mean squared error, mean absolute error, and R-squared are employed to evaluate estimation models' correctness. Among these models, XGBoost model has the highest prediction accuracy and can reduce 2134 (g) of wasted ink for each work. Thus, this study motivates machine learning's potential to help advance productivity and protect the environment.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.4A
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• pp.611-620
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• 2006

The composite two plate-girder bridges are generally defined as a non-redundant load path structure because the bridge can collapse if one of the two girders is seriously damaged by a fatigue crack. In this paper, a numerical study on the evaluation of the after-fracture redundancy of the composite two-girder bridges was accomplished. The evaluation has been performed on the simple and three-span continuous bridges with I-section cross beams which serve as transverse bracing, and with or without the bottom lateral bracing system. The load carrying capacities of the intact and damaged bridges with or without lateral bracing were evaluated from material and geometric nonlinear analysis, respectively and the redundancy was evaluated for each case. It was acknowledged from the analytical results that both simple and continuous intact two-girder bridges have sufficient redundancy even without lateral bracing, but it takes an important role to improve the redundancy of damaged bridges.

• Journal of Advanced Navigation Technology
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• v.28 no.4
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• pp.386-392
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• 2024

This paper constructs a precise dynamics model using flightlab, a specialized program for rotor modeling and performance analysis, to simulate urban air mobility (UAM). flightlab is well-suited for detailed modeling of UAM, particularly requiring detailed aerodynamic characteristics under high-altitude and urban wind conditions. The study focuses on implementing and analyzing a lift-cruise UAM model with distributed propulsion using flightlab. The lift-cruise model integrates motors for vertical take-off and fixed-wing flight. Given the limited specific examples of such UAM models in flightlab and challenges in evaluating with conventional fixed-wing or drone models, this research implements and verifies the lift-cruise model using matlab, comparing its performance against flightlab results to validate the modeling approach. This research aims to explore the potential of flightlab for detailed UAM modeling and contribute to technological advancements in future urban transportation.

• Journal of Korean Society of Environmental Engineers
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• v.29 no.6
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• pp.706-714
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• 2007

This study suggested a method for prediction of residual chlorine and THMs in water distribution system by measurement of residual chlorine, THMs, and other parameters, estimation of chlorine decay coefficients and THM formation coefficients, and simulation of water qualities using pipe network analysis. Bulk decay coefficients of parallel first-order were obtained by bottle tests, and pipe wall decay coefficients of first-order were estimated through evaluation of 5 models, which showed the lowest values of 0.03 for MAE(mean absolute error) and 0.037 MAE in comparison with the observed in field. And bottle tests were conducted to model first-order reaction of THM formation by nonlinear least square regression and the resultant coefficients were compared with the observed in field. As a result, the coefficients of determination$(R^2)$ for the observed and the predicted values were 0.98 in September and 0.82 in November, and the formation of THMs was predicted by modeling.

• Earthquakes and Structures
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• v.12 no.4
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• pp.397-407
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• 2017

To estimate the structural seismic demand, some methods are based on an equivalent linear system such as the Capacity Spectrum Method, the N2 method and the Equivalent Linearization method. Another category, widely investigated, is based on displacement correction such as the Displacement Coefficient Method and the Coefficient Method. Its basic concept consists in converting the elastic linear displacement of an equivalent Single Degree of Freedom system (SDOF) into a corresponding inelastic displacement. It relies on adequate modifying or reduction coefficient such as the inelastic deformation ratio which is usually developed for systems with known ductility factors ($C_{\mu}$) and ($C_R$) for known yield-strength reduction factor. The present paper proposes a rational approach which estimates this inelastic deformation ratio for SDOF bilinear systems by rigorous nonlinear analysis. It proposes a new inelastic deformation ratio which unifies and combines both $C_{\mu}$ and $C_R$ effects. It is defined by the ratio between the inelastic and elastic maximum lateral displacement demands. Three options are investigated in order to express the inelastic response spectra in terms of: ductility demand, yield strength reduction factor, and inelastic deformation ratio which depends on the period, the post-to-preyield stiffness ratio, the yield strength and the peak ground acceleration. This new inelastic deformation ratio ($C_{\eta}$) is describes the response spectra and is related to the capacity curve (pushover curve): normalized yield strength coefficient (${\eta}$), post-to-preyield stiffness ratio (${\alpha}$), natural period (T), peak ductility factor (${\mu}$), and the yield strength reduction factor ($R_y$). For illustrative purposes, instantaneous ductility demand and yield strength reduction factor for a SDOF system subject to various recorded motions (El-Centro 1940 (N/S), Boumerdes: Algeria 2003). The method accuracy is investigated and compared to classical formulations, for various hysteretic models and values of the normalized yield strength coefficient (${\eta}$), post-to-preyield stiffness ratio (${\alpha}$), and natural period (T). Though the ductility demand and yield strength reduction factor differ greatly for some given T and ${\eta}$ ranges, they remain take close when ${\eta}>1$, whereas they are equal to 1 for periods $T{\geq}1s$.