• Structural Engineering and Mechanics
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• v.29 no.2
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• pp.223-235
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• 2008

This paper focuses on the application of artificial neural networks (ANN) for optimal design of tensegrity grid as light-weight roof structures. A tensegrity grid, 2 m ${\times}$ 2 m in size, is fabricated by integrating four single tensegrity modules based on half-cuboctahedron configuration, using galvanised iron (GI) pipes as struts and high tensile stranded cables as tensile elements. The structure is subjected to destructive load test during which continuous monitoring of the prestress levels, key deflections and strains in the struts and the cables is carried out. The monitored structure is analyzed using finite element method (FEM) and the numerical model verified and updated with the experimental observations. The paper then explores the possibility of applying ANN based on multilayered feed forward back propagation algorithm for designing the tensegrity grid structure. The network is trained using the data generated from a finite element model of the structure validated through the physical test. After training, the network output is compared with the target and reasonable agreement is found between the two. The results demonstrate the feasibility of applying the ANNs for design of the tensegrity structures.

• Computers and Concrete
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• v.24 no.6
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• pp.561-570
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• 2019

Understanding the realistic behavior of concrete up to failure under different loading conditions within the framework of damage mechanics and plasticity would lead to an enhanced design of concrete structures. In the present investigation, QR (Quick Response) code based random speckle pattern is used as a non-contact sensor, which is an innovative approach in the field of digital image correlation (DIC). A four-point bending test was performed on RC beams of size 1800 mm × 150 mm × 200 mm. Image processing was done using an open source Ncorr algorithm for the results obtained using random speckle pattern and QR code based random speckle pattern. Load-deflection curves of RC beams were plotted for the results obtained using both contact and non-contact (DIC) sensors, and further, Moment (M)-Curvature (κ) relationship of RC beams was developed. The loading curves obtained were used as input data for material model parameters in finite element analysis. In finite element method (FEM) based software, concrete damage plasticity (CDP) constitutive model is used to predict the realistic nonlinear quasi-static flexural behavior of RC beams for monotonic loading condition. The results obtained using QR code based DIC are observed to be on par with conventional results and FEM results.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.7 no.4
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• pp.622-632
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• 1995

The present numerical study is aimed to investigate time-dependent characteristics of a two-dimensional lid-driven square cavity flow of three high Reynolds numbers, $7.5{\times}10^3$, $10^4$ and $3{\times}10^4$. A conservative convection term on irregular grids was adopted by renewing the MAC type difference schemes on regular grids. Relaxation of velocity and pressure is implemented by SOLA algorithm. In case of $Re=7.5{\times}10^3$, flow behavior converges to steady state after a transient period. But for $Re=10^4$, periodic unsteady sinusoidal fluctuation of local velocity and kinetic energy is found and continuous movements of small eddies in the secondary flow regions are also discovered. Random generation of eddies and their active migrating behavior are detected for $Re=3{\times}10^4$, resulting in complete unsteady and non-linear flow characteristics. And, an organized structure similar to a Moffat vortex is also observed from the time-mean flow patterns. Furthermore, a typoon-like vortex(TLV) appears intemittently and rotates along the separation regions and boundary layers.

• ETRI Journal
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• v.32 no.4
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• pp.512-519
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• 2010

A cooperative model is presented to enable sharing of the spectrum with secondary users. Compared with the optimal model and competitive model, the cooperative model could reach the maximum total profit for secondary users with better fairness. The cooperative model is built based on the Nash equilibrium. Then a conceding factor is introduced so that the total spectrum required from secondary users will decrease. It also results in a decrease in cost which the primary user charges to the secondary users. The optimum solution, which is the maximum total profit for the secondary users, is called the collusion state. It is possible that secondary users may leave the collusion state to pursue the maximum of individual profit. The stability of the algorithm is discussed by introducing a vindictive factor to inhabit the motive of deviation. In practice, the number of secondary users may change. Adaptive methods have been used to deal with the changing number of secondary users. Both the total profit and fairness are considered in the spectrum allocating. The shared spectrum is 11.3893 with a total profit of 65.2378 in the competitive model. In the cooperative model, the shared spectrum is 8.5856 with the total profit of 73.4963. The numerical results reveal the effectiveness of the cooperative model.

• Transactions on Control, Automation and Systems Engineering
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• v.3 no.1
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• pp.43-50
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• 2001

In this paper, we propose the design procedure of advance Polynomial Neural Networks(PNN) architecture for optimal model identification of complex and nonlinear system. The proposed PNN architecture is presented as the generic and advanced type. The essence of the design procedure dwells on the Group Method of Data Handling(GMDH). PNN is a flexible neural architecture whose structure is developed through learning. In particular, the number of layers of the PNN is not fixed in advance but is generated in a dynamic way. In this sense, PNN is a self-organizing network. With the aid of three representative numerical examples, compari-sons show that the proposed advanced PNN algorithm can produce the model with higher accuracy than previous other works. And performance index related to approximation and generalization capabilities of model is evaluated and also discussed.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.2
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• pp.203-208
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• 1998

This paper presents an adaptive fuzzy controller using an neural network and adaptation algorithm. Reference-model following neuro-fuzzy controller(RMFNFC) is invesgated in order to overcome the difficulty of rule selecting and defects of the membership function in the general fuzzy logic controller(FLC). RMFNFC is developed to tune various parameter of the fuzzy controller which is used for the discrete nonlinear system control. RMFNFC is trained with the identification information and control closed loop error. A closed loop error is used for design criteria of a fuzzy controller which characterizes and quantize the control performance required in the overall control system. A control system is trained up the controller with the variation of the system obtained from the identifier and closed loop error. Numerical examples are presented to control of the discrete nonlinear system. Simulation results show the effectiveness of the proposed controller.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.9
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• pp.916-921
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• 2009

The technology to inspect and measure an inner structure of micro parts has become an important tool in the semi-conductor industrial field with the development of automation and precision manufacturing. Especially, the inspection skill on the inside of highly integrated electronic device becomes a key role in detecting defects of a completely assembled product. X-ray inspection technology has been focused as a main method to inspect the inside structure. However, there has been insufficient research done on the customized inspection technology for the flip-chip assembly due to the interior connecting part of flip chip which connects the die and PCB electrically through balls positioned on the die. In this study, therefore, it is implemented to detect shape error of flip chip bonding without damaging chips using an x-ray inspection system. At this time, it is able to monitor the solder bump shape by introducing an edge-extracting algorithm (exponential approximation function) according to the attenuating characteristic and detect shape error compared with CAD data. Additionally, the bonding error of solder bumps is automatically detectable by acquiring numerical size information at the extracted solder bump edges.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.14 no.3
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• pp.349-359
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• 2001

An enhanced four-node plate element, which has been developed for explicit dynamic analysis of plate, is described in this paper. Reissner-Mind1in(RM) assumptions are adopted to consider transverse shear deformation effects in the present plate element. RM plate element produces a shear locking phenomena in thin plate so that the substitute natural strains based on assumed strain method are explicitly derived. The present plate element is applied into the explicit transient algorithm and the mass matrix of plate is formulated by using special lumping method proposed by Hinton et al. The performance of the element is verified with numerical examples.

• Corrosion Science and Technology
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• v.16 no.2
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• pp.64-68
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• 2017

The interactions between corrosion pits on stainless steel under loading conditions are studied by using a cellular automata model coupled with finite element method at a mesoscopic scale. The cellular automata model focuses on a metal/film/electrolyte system, including anodic dissolution, passivation, diffusion of hydrogen ions and salt film hydrolysis. The Chopard block algorithm is used to improve the diffusion simulation efficiency. The finite element method is used to calculate the stress concentration on the pit surface during pit growth, and the effect of local stress and strain on anodic current is obtained by using the Gutman model, which is used as the boundary conditions of the cellular automata model. The transient current characteristics of the interactions between corrosion pits under different simulation factors including the breakdown of the passive film at the pit mouth and the diffusion of hydrogen ions are analyzed. The analysis of the pit stability product shows that the simulation results are close to the experimental conclusions.

• Journal of the Korean Magnetics Society
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• v.27 no.3
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• pp.98-103
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• 2017

In this paper, an efficient closed-loop degaussing technique is proposed to control real-time degaussing currents required for a minesweeper. To achieve this, new principle and algorithm for controling degaussing currents are presented, and they are compared to conventional ones. To validate the proposed method, a minesweeper mockup is tested by means of a rigorous numerical simulation. Results show that the method successfully yields satisfactory degaussing performances for several course angle changes of the mockup.