• Composites Research
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• v.16 no.1
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• pp.13-18
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• 2003

Prediction of composite fatigue life is not a straightforward matter, depending on various failure modes and their interactions. In this paper, a methodology is presented to predict fatigue life and residual strength of composite materials based on Phenomenological Model(non-linear fatigue damage model). It is assumed that the residual strength is a monotonically decreasing function of the number of loading cycles and applied fatigue stress ratio and the model parameters(strength degradation parameter and fatigue shape parameter) are assumed as function of fatigue life. Then S-N curve is used to extract model parameters that are required to characterize the stress levels comprising a randomly-ordered load spectrum. Different stress ratios (${\sigma}_{min}/{\;}{\sigma}_{max}$) are handled with Goodman correction approach(fatigue envelope) and the residual strength after an arbitrary load cycles is represented by two parameter weibull functions.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.7
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• pp.16-24
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• 1999

This paper deals with the dynamic vehicle arbitration algorithm for communication between vehicles and a roadside control init on multilane environment. The suggested algorithm varies its parameter values according to the current vehicle arrival rate to get the maximum performance. To get the optimum parameter values, arbitration methods that use random delay counter and persist mechanism were taken into account and the performance of these methods with respect to the vehicle arrival rate was analyzed by computer simulation. After applying the optimum parameter values to suggested algorithm, it is shown that more enhanced reliability was acquired This algorithm could be applied to various systems which include the communication between a transponder and a control unit.

• Computational Structural Engineering
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• v.10 no.2
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• pp.149-160
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• 1997

Mechanical structures are composed of substructures connected by joints and boundary elements. While the finite element representation of plain substructures is well developed and reliable, joints have a lot of uncertainties in being accurately modelled and affect dynamic behavior of a total system. In order to improve the accuracy of a finite element model, a new method is proposed, in which reduced finite element model is combined with a system identification technique. After substructures except joints are modelled with finite element method and joint properties are represented by parameter states, non-linear state equation is derived in which parameter states are multiplied by physical states such as displacements and velocities. So the joint parameter identification is transformed into non-linear state estimation problem. The methods are tested and discussed numerically and the feasibility for physical application has been demonstrated through two example structures.

• Journal of Aerospace System Engineering
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• v.11 no.6
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• pp.17-25
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• 2017

Vertical reaction force between ground and tire is an important parameter determining the ground behavior characteristics of aircraft. This parameter can be used to calculate the lateral force and friction. However, it is hard to obtain this parameter in real-time when the aircraft is taxiing. Therefore, pre-analysis of ground behavior and vertical reaction force should be conducted using ground simulation results to prevent rollover or hazardous scenarios. In this paper, a Landing Gear and Full-Aircraft model was constructed using VI-Aircraft S/W. The roll behavior of aircraft was analyzed using steering simulation results compared with taxi-test data.

• Steel and Composite Structures
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• v.29 no.5
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• pp.579-590
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• 2018

Size-dependent free vibration responses and magneto-electro-elastic bending results of a three layers piezomagnetic curved beam rest on Pasternak's foundation are presented in this paper. The governing equations of motion are derived based on first-order shear deformation theory and nonlocal piezo-elasticity theory. The curved beam is containing a nanocore and two piezomagnetic face-sheets. The piezomagnetic layers are imposed to applied electric and magnetic potentials and transverse uniform loadings. The analytical results are presented for simply-supported curved beam to study influence of some parameters on vibration and bending results. The important parameters are spring and shear parameters of foundation, applied electric and magnetic potentials, nonlocal parameter and radius of curvature of curved beam. It is concluded that the increase in radius of curvature tends to an increase in the stiffness of curved beam and consequently natural frequencies increase and bending results decrease. In addition, it is concluded that with increase of nonlocal parameter of curved beam, the stiffness of structure is decreased that leads to decrease of natural frequency and increase of bending results.

• Korean Journal of Metals and Materials
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• v.49 no.4
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• pp.329-333
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• 2011

To develop wide-band noise absorbers with a special design for low-frequency performance, this study proposes a tin oxide (Sn-O) thin films as the noise absorbing materials in a microstrip line. Sn-O thin films were deposited on polyimide film substrates by reactive sputtering of the Sn target under flowing $O_{2}$ gas, exhibiting a wide variation of surface resistance (in the range of $10^{0}-10^{5}{\Omega}$) depending on the oxygen partial pressure during deposition. The microstrip line with characteristic impedance of $50\Omega$ was used for the measurement of noise absorption by the Sn-O films. The reflection parameter $(S_{11})$ increased with a decrease of surface resistance due to an impedance mismatch at the boundary between the film and the microstrip line. Meanwhile, the transmission parameter $(S_{21})$ diminished with a decrease of surface resistance resulting from an Ohmic loss of the Sn-O films. The maximum noise absorption predicted at an optimum surface resistance of the Sn-O films was about $150{\Omega}$. For this film, greater power absorption is predicted in the lower frequency region (about 70% at 1 GHz) than in conventional magnetic sheets of high magnetic loss, indicating that Ohmic loss is the predominant loss parameter for the conduction noise absorption in the low frequency band.

• Nuclear Engineering and Technology
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• v.53 no.8
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• pp.2708-2715
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• 2021

The Multi-Purpose Overload Robot (CMOR) is a key subsystem of China Fusion Engineering Test Reactor (CFETR) remote handling system. Due to the long cantilever and large loads of the CMOR, it has a large rigid-flexible coupling deformation that results in a poor position accuracy of the end-effector. In this study, based on the Levenberg-Marquardt algorithm, the spatial grid, and the linearized variable load principle, a variable parameter compensation model was designed to identify the parameters of the CMOR's kinematics models under different loads and at different poses so as to improve the trajectory tracking accuracy. Finally, through Adams-MATLAB/Simulink, the trajectory tracking accuracy of the CMOR's rigid-flexible coupling model was analyzed, and the end position error exceeded 0.1 m. After the variable parameter compensation model, the average position error of the end-effector became less than 0.02 m, which provides a reference for CMOR error compensation.

• International Journal of Computer Science & Network Security
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• v.24 no.2
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• pp.150-154
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• 2024

In recent years, there are extensive researches on the applications of machine learning to the automation and decision support for medical experts during disease detection. However, the performance of machine learning still needs improvement so that machine learning model produces result that is more accurate and reliable for disease detection. Selecting the hyper-parameter that could produce the possible maximum classification accuracy on medical dataset is the most challenging task in developing decision support systems with machine learning algorithms for medical dataset classification. Moreover, selecting the features that best characterizes a disease is another challenge in developing machine-learning model with better classification accuracy. In this study, we have proposed an optimized decision tree model for heart disease classification by using heart disease dataset collected from kaggle data repository. The proposed model is evaluated and experimental test reveals that the performance of decision tree improves when an optimal number of features are used for training. Overall, the accuracy of the proposed decision tree model is 98.2% for heart disease classification.

• Advances in materials Research
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• v.13 no.1
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• pp.1-18
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• 2024

The present experimental investigation focuses on finding optimal parametric data-set of laser micro-drilling operation with minimum taper and Heat-affected zone during laser micro-drilling of Carbon Nanotube/Epoxy-based composite materials. Experiments have been conducted as per Box-Behnken design (BBD) techniques considering cutting speed, lamp current, pulse frequency and air pressure as input process parameters. Then, the relationship between control parameters and output responses is developed using second-order nonlinear regression models. The analysis of variance test has also been performed to check the adequacy of the developed mathematical model. Using the Response Surface Methodology (RSM) and an Accelerated particle swarm optimization (APSO) technique, optimum process parameters are evaluated and compared. Moreover, confirmation tests are conducted with the optimal parameter settings obtained from RSM and APSO and improvement in performance parameter is noticed in each case. The optimal process parameter setting obtained from predictive RSM based APSO techniques are speed=150 (m/s), current=22 (amp), pulse frequency (3 kHz), Air pressure (1 kg/cm²) for Taper and speed=150 (m/s), current=22 (amp), pulse frequency (3 kHz), air pressure (3 kg/cm²) for HAZ. From the confirmatory experimental result, it is observed that the APSO metaheuristic algorithm performs efficiently for optimizing the responses during laser micro-drilling process of nanocomposites both in individual and multi-objective optimization.

• Progress in Superconductivity
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• v.8 no.2
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• pp.143-151
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• 2007

Accurate measurements of the microwave surface resistance (Rs) of high temperature superconductor (HTS) films are important with regard to applications of HTS materials for wireless communications. As the surface resistance values of HTS films are usually extracted from the measured unloaded quality factor ($Q_0$) of resonators made of HTS films, it is essential to measure the resonator $Q_0$ with accuracy. The $TE_{011}\;mode\;Q_0$ of sapphire resonators with the endplates made of $YBa_2Cu_3O_{7-{\delta}}$(YBCO) film on $LaAlO_3$ is measured by using the S-parameter circle-fit method at a frequency of about 19.6 GHz and temperatures of 30 K to 90 K, which is compared with the measured values by using the Lorentzian-fit method. Good agreements are found between the two sets of $Q_0$ values measured by using the two different methods whether the resonator is used in a weak-coupling scheme or a strong-coupling scheme, showing reliability of both methods fur measuring the resonator $Q_0$ accurately. The $Q_0$ of sapphire resonators with a gap between the top plate and the rest of the resonator is also discussed.