• Computers and Concrete
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• v.33 no.2
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• pp.163-173
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• 2024

Fiber-reinforced polymers (FRP) have a proven strength enhancement capability when installed into Reinforced Concrete (RC) beams. The brittle failure of traditional FRP strengthening systems has attracted researchers to develop novel materials with improved strength and ductility properties. One such material is that known as polyethylene terephthalate (PET). This study presents a numerical investigation of the flexural behavior of reinforced concrete beams externally strengthened with PET-FRP systems. This material is distinguished by its large rupture strain, leading to an improvement in the ductility of the strengthened structural members compared to conventional FRPs. A three-dimensional (3-D) finite element (FE) model is developed in this study to predict the load-deflection response of a series of experimentally tested beams published in the literature. The numerical model incorporates constitutive material laws and bond-slip behavior between concrete and the strengthening system. Moreover, the validated model was applied in a parametric study to inspect the effect of concrete compressive strength, PET-FRP sheet length, and reinforcing steel bar diameter on the overall performance of concrete beams externally strengthened with PET-FRP.

• Nuclear Engineering and Technology
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• v.54 no.11
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• pp.4373-4391
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• 2022

Marine reactor systems experience platform movement, and therefore, the system thermal-hydraulic analysis code needs to reflect the motion effect on the fluid to evaluate reactor safety. A moving reactor model for MARS-KS was developed to simulate the hydrodynamic phenomena in the reactor under motion conditions; however, its applicability does not cover the MULTID component used in multidimensional flow analyses. In this study, a moving reactor model is implemented for the MULTID component to address the importance of multidimensional flow effects under dynamic motion. The concept of the volume connection is generalized to facilitate the handling of the junction of MULTID. Further, the accuracy in calculating the pressure head between volumes is enhanced to precisely evaluate the additional body force. Finally, the Coriolis force is modeled in the momentum equations in an acceleration form. The improvements are verified with conceptual problems; the modified model shows good agreement with the analytical solutions and the computational fluid dynamic (CFD) simulation results. Moreover, a simplified gravity-driven injection is simulated, and the model is validated against a ship flooding experiment. Throughout the verifications and validations, the model showed that the modification was well implemented to determine the capability of multidimensional flow analysis under ocean conditions.

• Smart Structures and Systems
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• v.15 no.4
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• pp.1103-1120
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• 2015

A self-sensing magnetorheological (MR) damper with embedded piezoelectric force sensor has recently been devised to facilitate real-time close-looped control of structural vibration in a simple and reliable manner. The development and characterization of the self-sensing MR damper are presented based on experimental work, which demonstrates its reliable force sensing and controllable damping capabilities. With the use of experimental data acquired under harmonic loading, a nonparametric dynamic model is formulated to portray the nonlinear behaviors of the self-sensing MR damper based on NARX modeling and neural network techniques. The Bayesian regularization is adopted in the network training procedure to eschew overfitting problem and enhance generalization. Verification results indicate that the developed NARX network model accurately describes the forward dynamics of the self-sensing MR damper and has superior prediction performance and generalization capability over a Bouc-Wen parametric model.

• Journal of The Korean Society of Agricultural Engineers
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• v.63 no.1
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• pp.103-116
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• 2021

Analysis of runoff is substantial for effective water management in the watershed. Runoff occurs by reaction of a watershed to the rainfall and has non-linearity and uncertainty due to the complex relation of weather and watershed factors. ANN (Artificial Neural Network), which learns from the data, is one of the machine learning technique known as a proper model to interpret non-linear data. The performance of ANN is affected by the ANN's structure, the number of hidden layer nodes, learning rate, and activation function. Especially, the activation function has a role to deliver the information entered and decides the way of making output. Therefore, It is important to apply appropriate activation functions according to the problem to solve. In this paper, ANN models were constructed to estimate runoff with different activation functions and each model was compared and evaluated. Sigmoid, Hyperbolic tangent, ReLU (Rectified Linear Unit), ELU (Exponential Linear Unit) functions were applied to the hidden layer, and Identity, ReLU, Softplus functions applied to the output layer. The statistical parameters including coefficient of determination, NSE (Nash and Sutcliffe Efficiency), NSEln (modified NSE), and PBIAS (Percent BIAS) were utilized to evaluate the ANN models. From the result, applications of Hyperbolic tangent function and ELU function to the hidden layer and Identity function to the output layer show competent performance rather than other functions which demonstrated the function selection in the ANN structure can affect the performance of ANN.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.3 no.3
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• pp.309-330
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• 2009

In this paper, we introduce the architecture of Genetic Algorithm(GA) based Feed-forward Polynomial Neural Networks(PNNs) and discuss a comprehensive design methodology. A conventional PNN consists of Polynomial Neurons, or nodes, located in several layers through a network growth process. In order to generate structurally optimized PNNs, a GA-based design procedure for each layer of the PNN leads to the selection of preferred nodes(PNs) with optimal parameters available within the PNN. To evaluate the performance of the GA-based PNN, experiments are done on a model by applying Medical Imaging System(MIS) data to a multi-variable software process. A comparative analysis shows that the proposed GA-based PNN is modeled with higher accuracy and more superb predictive capability than previously presented intelligent models.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.3
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• pp.150-162
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• 2022

This study investigated the impact of the latest developments in big data analytics capabilities (BDAC) on firm performance. The BDAC have the power to innovate existing management practices. Nevertheless, their impact on firm performance has not been fully is not yet fully elucidated. The BDAC relates to the flexibility of infrastructure as well as the skills of management and firm's personnel. Most studies have explored the phenomena from a theoretical perspective or based on factors such as organizational characteristics. However, this study extends the flow of previous research by proposing and testing a model which examines whether organizational exploration, exploitation and market agility mediate the relationship between the BDAC and firm performance. The proposed model was tested using survey data collected from the long-term employees over 10 years in 250 companies. The results analyzed through structural equation modeling show that a strong BDAC can help improve firm performance. An organization's ability to analyze big data affects its exploration and exploitation thereby affecting market agility, and, consequently, firm performance. These results also confirm the powerful mediating role of exploration, exploitation, and market agility in improving insights into big data utilization and improving firm performance.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.313-316
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• 2016

Highly probable cause of the current turmoil critical national infrastructure and private enterprise information systems failures or national event of an accident, it is inevitable huge hit in corporate business as well as a significant impact on the national benefit. This is a trend subject to the stability of the national management information system has a significant impact on people and society, such as banking, telecommunications, transport and energy, which can be extended into a private institution. However, public and private ICT business through the development of Information system Audit or CMMI(Capability Maturity Model Integration) certification check the quality of the target system, but quality check on the reliability of the information system operations after construction is either not promoting met for some safety test results a situation that does not enabled by insufficient. By preventing the disorder or an accident of this study, the diagnostic reliability information systems through inspection and evaluation system development of information systems being established, and to minimize service confusion and study ways to ensure customer - oriented service.

• Structural Engineering and Mechanics
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• v.70 no.3
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• pp.289-301
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• 2019

Hysteretic energy is defined as energy dissipated through inelastic deformations during a ground motion by the system. It includes frequency content and duration of ground motion as two remarkable parameters, while these characteristics are not seen in displacement spectrum. Since maximum displacement individually cannot be the appropriate criterion for damage assessment, hysteretic energy has been evaluated in this research as a more comprehensive seismic demand parameter. An innovative methodology has been proposed to establish a new equivalent linear model to estimate hysteretic energy spectrum for bilinear SDOF models under two different sets of earthquake excitations. Error minimization has been defined in the space of equivalent linearization concept, which resulted in equivalent damping and equivalent period as representative parameters of the linear model. Nonlinear regression analysis was carried out for predicting these equivalent parameter as a function of ductility. The results also indicate differences between seismic demand characteristics of far-field and near-field ground motions, which are not identified by most of previous equations presented for predicting seismic energy. The main advantage of the proposed model is its independency on parameters related to earthquake and response characteristics, which has led to more efficiency as well as simplicity. The capability of providing a practical energy based seismic performance evaluation is another outstanding feature of the proposed model.

• Journal of Mechanical Science and Technology
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• v.20 no.4
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• pp.437-446
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• 2006

Laser vision inspection systems are becoming popular for automated inspection of manufactured components. The performance of such systems can be enhanced by improving accuracy of the hardware and robustness of the software used in the system. This paper presents a new approach for enhancing the capability of a laser vision system by applying hardware compensation and using efficient analysis software. A 3D geometrical model is developed to study and compensate for possible distortions in installation of gantry robot on which the vision system is mounted. Appropriate compensation is applied to the inspection data obtained from the laser vision system based on the parameters in 3D model. The present laser vision system is used for dimensional inspection of car chassis sub frame and lower arm assembly module. An algorithm based on simplex search techniques is used for analyzing the compensated inspection data. The details of 3D model, parameters used for compensation and the measurement data obtained from the system are presented in this paper. The details of search algorithm used for analyzing the measurement data and the results obtained are also presented in the paper. It is observed from the results that, by applying compensation and using appropriate algorithms for analyzing, the error in evaluation of the inspection data can be significantly minimized, thus reducing the risk of rejecting good parts.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.320-325
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• 1998

Underwater robotic vehicles (URVs) have been an important tool for various underwater tasks because they have greater speed, endurance, depth capability, and safety than human divers. As the use of such vehicles increases, the vehicle control system becomes one of the most critical subsytems to increase autonomy of the vehicle. The vehicle dynamics are nonlinear and their hydrodynamic coefficients are often difficult to estimate accurately. In this paper a new type of fuzzy model-based controller based on Takagi-Sugeno-Kang fuzzy model is designed and applied to the control of of an underwater robotic vehicle. The proposed fuzzy controller : 1) is a nonlinear controller, but a linear state feedback controller in the consequent of each local fuzzy control rule ; 2) can guarantee the stability of the closed-loop fuzzy system ; 3) is relatively easy to implement. Its good performance as well as its robustness to the change of parameters have been shown and compared with the re ults of conventional linear controller by simulation.