• Journal of KSNVE
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• v.6 no.4
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• pp.475-479
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• 1996

Recently, fiber optic hydrophone is a subject which has attracted as a underwater acoustic sensor. In this paper, a length of optical fiber is bonded to an end-capped hollow cylinder of some elastic material, e. g. aluminum and glass-pyres. The normalized sensitivity is derived according to the direction of polarization. Derived sensitivity equations are simulated for two different mandrel materials. The results are also compared to the McMahon's results which calculated for an average Pockel coefficient. Based on the numerical simulation normalized sensitivity is propotional to the inner to outer diameter ratio.

• Journal of the Korean Society for Nondestructive Testing
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• v.29 no.6
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• pp.563-569
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• 2009

In this paper, four different types of pulsed eddy current(PEC) probe are designed and their performance of detecting wall thickness reduction is compared. By using the backward difference method in time and the finite element method in space, PEC signals from various thickness and materials are numerically calculated and three features of the signal are selected. Since PEC signals and features are obtained by various types and sizes of probe, the comparison is made through the normalized features which reflect the sensitivity of the feature to thickness reduction. The normalized features indicate that the shielded reflection probe provides the best sensitivity to wall thickness reduction for all three signal features. Results show that the best sensitivity to thickness reduction can be achieved by the peak value, but also suggest that the time to peak can be a good candidate because of its linear relationship with the thickness variation.

• Structural Engineering and Mechanics
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• v.70 no.2
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• pp.209-219
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• 2019

By normalizing the internal hysteresis variable and eliminating the redundant parameter, the normalized Bouc-Wen model is considered to be an improved and more reasonable form of the Bouc-Wen model. In order to facilitate application and further research of the normalized Bouc-Wen model, some key aspects of the model need to be uncovered. In this paper, hysteresis characterization of the normalized Bouc-Wen model is first studied with respect to the model parameters, which reveals the influence of each model parameter to the shape of the hysteresis loops. The parameter identification scheme is then proposed based on an improved genetic algorithm (IGA), and verified by experimental test data. It is proved that the proposed method can be an efficacious tool for identification of the model parameters by matching the reconstructed hysteresis loops with the target hysteresis loops. Meanwhile, the IGA is shown to outperform the standard GA. Finally, a simplified identification method is proposed based on parameter sensitivity, which indicates that the efficiency of the identification process can be greatly enhanced while maintaining comparable accuracy if the low-sensitivity parameters are reasonably restricted to narrower ranges.

• Journal of Welding and Joining
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• v.27 no.5
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• pp.81-87
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• 2009

Recently, extruded aluminium-alloy panels have been used in the car bodies for the purpose of the light-weight of railway vehicles and FSW(Friction Stir Welding), which is superior to the arc weldings, has been applied in the railway vehicles. This paper presents the optimum design of the FSW process on A6005 extruded alloy for railway vehicles to improve its mechanical properties. Rotational speed, welding speed and tilting angle of the tool tip were chosen as design parameters. Three objective functions were determined; maximizing the tensile strength, minimizing the hardness and maximizing the difference between the normalized tensile strength and hardness. The tensile tests and the hardness tests for fifteen FSW experiments were carried out according to the central composite design table. Recursive model functions on three characteristic values, such as the tensile strength, the hardness difference(${\Delta}Hv$) and the difference of normalized tensile strength and ${\Delta}Hv$, were estimated according to the classical response surface analysis methodology. The reliability of each recursive function was verified by F-test using the analysis of variance table. Sensitivity analysis on each characteristic value was done. Finally, the optimum values of three design parameters were found using Sequential Quadratic Programming algorithm.

• Journal of Sensor Science and Technology
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• v.27 no.1
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• pp.25-30
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• 2018

Closed-form analytical expressions and 3-dimensional normalized charts for the homogeneous sensing and surface sensing structures are derived to provide the conditions for the maximum sensitivity of integrated-optic biosensors based on evanescent-wave and stepindex planar optical waveguides. The analysis is made for transverse electric (TE) polarization mode, in both cases where the measurand is homogeneously distributed in the cover (namely, homogeneous sensing), and where it is an ultrathin film on the waveguide-cover interface (namely, surface sensing).

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.21 no.9
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• pp.50-55
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• 2022

Acceleration performance, maximum velocity, urban driving energy consumption, and high-way driving energy consumption are important characteristics of electric vehicle driving. This study analyzes the effect of a gear ratio on these characteristics for a front wheel drive electric vehicle. The normalized sensitivity metric is used to compare the sensitivity of these scaled characteristics to the changes in the gear ratio. The sensitivity analysis results show that the normalized values are 0.95 for maximum velocity, 0.91 for acceleration performance, 0.51 for urban driving energy consumption, and 0.24 for high-way driving energy consumption. Therefore, the maximum velocity was affected the most by the changes in the gear ratio. These results can be used to determine the gear ratio of a front wheel drive electric vehicle to optimize the driving characteristics simultaneously.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.9
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• pp.4253-4258
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• 2012

The investigation of the undrained strength and the important several undrained geotechnical properties was, in detail, made for highly plastic soils using the field and laboratory testing results. The plastic index, activity, water content, and effective unit weight did not show the notable relationship with both Su and normalized Su. The OCR, sensitivity, and undrained elastic modulus presented remarkable tendency with normalized Su. It could be concluded that the use of the normalized Su may lead to the reasonable results then the normalized Su needs further research.

• Journal of Korea Water Resources Association
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• v.39 no.8 s.169
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• pp.677-690
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• 2006

The LH-OAT (Latin Hypercube One factor At a Time) method for sensitivity analysis and SCE-UA (Shuffled Complex Evolution at University of Arizona) optimization method were applied for the automatic calibration of SWAT model in Bocheong-cheon watershed. The LH-OAT method which combines the advantages of global and local sensitivity analysis effectively identified the sensitivity ranking for the parameters of SWAT model over feasible parameter space. Use of this information allows us to select the calibrated parameters for the automatic calibration process. The performance of the automatic calibration of SWAT model using SCE-UA method depends on the length of calibration period, the number of calibrated parameters, and the selection of statistical error criteria. The performance of SWAT model in terms of RMSE (Root Mean Square Error), NSEF (Nash-Sutcliffe Model Efficiency), RMAE (Relative Mean Absolute Error), and NMSE (Normalized Mean Square Error) becomes better as the calibration period and the number of parameters defined in the automatic calibration process increase. However, NAE (Normalized Average Error) and SDR (Standard Deviation Ratio) were not improved although the calibration period and the number of calibrated parameters are increased. The result suggests that there are complex interactions among the calibration data, the calibrated parameters, and the model error criteria and a need for further study to understand these complex interactions at various representative watersheds.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.360-365
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• 1993

In this paper, we propose a new design procedure of the Robust Model Matching(RM) using the Normalized Left Coprime Factorization (NLCF) approach. The RMM aims at reducing the sensitivity of a given control system, but standard design procedures are not for robust stability. Therefore we try applying the robust stability condition based on NLCF to RMM procedure. We first formulate the RMM using the robust stability condition of NLCF approach, then we propose the new procedure of the RMM. The point is that the condition includes the measure of sensitivity of the RMM. In the proposed procedure, a cost function is determined through the condition and solved by H$_{\infty}$ contro technique. Finally we show a design example and check the performance..

• International Journal of Concrete Structures and Materials
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• v.6 no.2
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• pp.101-110
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• 2012

This paper focuses on the finite element (FE) response sensitivity and reliability analyses considering smooth constitutive material models. A reinforced concrete frame is modeled for FE sensitivity analysis followed by direct differentiation method under both static and dynamic load cases. Later, the reliability analysis is performed to predict the seismic behavior of the frame. Displacement sensitivity discontinuities are observed along the pseudo-time axis using non-smooth concrete and reinforcing steel model under quasi-static loading. However, the smooth materials show continuity in response sensitivity at elastic to plastic transition points. The normalized sensitivity results are also used to measure the relative importance of the material parameters on the structural responses. In FE reliability analysis, the influence of smoothness behavior of reinforcing steel is carefully noticed. More efficient and reasonable reliability estimation can be achieved by using smooth material model compare with bilinear material constitutive model.