• Proceedings of the Korean Society For Composite Materials Conference
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• 2002.10a
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• pp.75-78
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• 2002

A simplified methodology is presented to predict fatigue life and residual strength of composite structures. To avoid excessive amount of tests that are required for model characterization, strength degradation parameter is assumed as function of fatigue life. S-N curve is used to extract fatigue life that is required to characterize the stress levels comprising a randomly-ordered load spectrum. And different stress ratios are handled with Goodman correction approach(fatigue envelope). It is assumed that the residual strength is a function of the number of loading cycles and applied fatigue stress amplitude. And the residual strength distribution after an arbitrary load cycles is represented by two parameter Weibull functions.

• Journal of Environmental Science International
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• v.4 no.5
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• pp.41-41
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• 1995

In order to discuss the differences among the SMP(Surface Moisture Availability Parameter), by previous researchers on the basis of their own theoretical and empirical background, we assessed the SMP according to the soil types and volumetric soil water contents. The results are as follows. There are differences among all the five SMAPs. There''s a tendency that the larger grain size, the higher value of parameters. And they divided into two groups for their value: one group has parameters with exponential function and the other with cosine and linear function. The maximum difference between the two groups appears when the volumetric soil water contents are 0.07$m^3m^{-3}$ for sand, 0.l1$m^3m^{-3}$ for loam, 0.12 for clay, and 0.13$m^3m^{-3}$ for silt loam. So, these differences must be considered when we estimate the surface evaporation rate. From field data, the paddy field soil around Junam reservoir is classified as a silt has high wetness, 0.56. So, the parameter obtained from the field measurement is much higher than that of Clapp and Hornberger(1978)''s Table. This study treated the SMP for a certain point of time in winter season. But if we measured the soil water contents continuously, we could obtain better time-dependent parameter.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1998.10a
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• pp.439-446
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• 1998

One of the most important roles in the nonlinear dynamic structural analysis is to select a proper ground excitation, which dominates the response of a structure. Because of the lack of recorded accelerograms in Korea, a stochastic model of ground excitation with various dynamic properties rather than recorded accelerograms is necessarily required. If all information is not available at site, the information from other sites with similar features can be used by the procedure of seismic hazard analysis. Eliopoulos and Wen identified the parameters of the ground motion model by the empirical relations or expressions developed by Trifunac and Lee. Because the relations used in the parameter identification are largely empirical, it is required to apply the artificial neural networks instead of the empirical model. Additionally, neural networks have the advantage of the empirical model that it can continuously re-train the new recorded data, so that it can adapt to the change of the enormous data. Based on the redefined traditional processes, three neural-networks-based models (FAS_NN, PSD_NN and INT_NN) are proposed to individually substitute the Fourier amplitude spectrum, the parameter identification of power spectral density function and intensity function. The paper describes the first half of the research for the development of Neural-Networks-based model for the generation of an Artificial earthquake and a Response Spectrum(NNARS).

• Journal of Information Technology Applications and Management
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• v.25 no.4
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• pp.115-122
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• 2018

Software reliability has the greatest impact on computer system reliability and software quality. For this software reliability analysis, In this study, we compare and analyze the trends of the properties affecting the reliability according to the shape parameters of Erlang distribution based on the finite fault NHPP. Software failure time data were used to analyze software failure phenomena, the maximum likelihood estimation method was used for parameter estimation. As a result, it can be seen that the intensity function is effective because it shows a tendency to decrease with time when the shape parameters a = 1 and a = 3. However, the pattern of the mean value function showed an underestimation pattern for the true values when the shape parameters a = 1 and a = 2, but it was found to be more efficient when a = 3 because the error width from the true value was small. Also, in the reliability evaluation of the future mission time, the stable and high trend was shown when the shape parameters a = 1 and a = 3, but on the contrary, when a = 2, the reliability decreased with the failure time. Through this study, the property of finite fault NHPP Erlang model according to the change of shape parameter without existing research case was newly analyzed, and new research information that software developers can use as basic guideline was presented.

• International Journal of Reliability and Applications
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• v.1 no.1
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• pp.81-87
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• 2000

One of the most important quantities in reliability theory is the expected number of renewals of a system during a given interval. This quantity, the renewal function, is used to determine the optimal preventive maintenance policy and to estimate the cost of a warranty. In this paper we study a parametric approach for a renewal function. The simulation study is presented to compare the relative performance of the introduced estimators of a renewal function. And we show that the proposed parametric estimator performs well.

• Journal of the Korean Data and Information Science Society
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• v.11 no.2
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• pp.181-188
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• 2000

The shape of an M-estimation function is generally determined in the sense of either/both maximizing efficiency of an M-estimator at the model or/and bounding the influence function of an M-estimator. We propose an empirical method of choosing a value of the bending constant in Huber's ${\psi}-function$, which is the most widely used M-estimation function when estimating the location parameter.

• Structural Engineering and Mechanics
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• v.20 no.6
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• pp.713-726
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• 2005

Based on the improved first order Taylor interval expansion, a new interval analysis method for the static or dynamic response of the structures with interval parameters is presented. In the improved first order Taylor interval expansion, the first order derivative terms of the function are also considered to be intervals. Combining the improved first order Taylor series expansion and the interval extension of function, the new interval analysis method is derived. The present method is implemented for a continuous beam and a frame structure. The numerical results show that the method is more accurate than the one based on the conventional first order Taylor expansion.

• 한국신재생에너지학회:학술대회논문집
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• 2009.06a
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• pp.512-515
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• 2009

This research describes on airfoil shape design, crucial to core technique and algorithm optimization for the wind turbine blade development. We grasped the parameter to define the airfoil shape in the wind turbine blade and aircraft, and the important performance characteristic of the airfoil. The airfoil shape function is selected by studying which is suitable for wind turbine blade airfoil development. The selected method is verified by to compare the generated airfoil shape with base airfoil. The new airfoils were created by the selecting shape function based on the well-known airfoil for wind turbine blades. In addition, we performed aerodynamic analysis about the generated airfoils by XFOIL and estimated the point of difference in the airfoil shape parameter using the aerodynamic performance results which is compared with basic airfoil. This result data applies to the fundamental research for a wind turbine blade optimization design and accomplished the aerodynamic analysis manual.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.483-487
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• 1994

In this paper, we analize the effect of a steering water used in a unified phase I-phase II semi-infinite constrained optimization algorithm and present a new algorithm based on the facts that when the point x is far away from the feasible region where all the constraints are satisfied, reaching to the feasible region is more important than minimizing the cost function and that when the point x is near the region, it is more efficient to try to reach the feasible region and to minimize the cost function concurrently. Also, the angle between the search direction vector and the gradient of the cost function is considered when the steering parameter value is computed. Even though changing the steering parameter does not change the rate of convergence of the algorithm, we show through some examples that the proposed algorithm performs better than the other algorithms.

• International Journal of Control, Automation, and Systems
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• v.4 no.4
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• pp.428-437
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• 2006

Many physical systems are hybrid in the sense that they have continuous behaviors and discrete phenomena. In control system with multiple models, switching strategy and stability of the closed-loop system under switching are very important issues. In this paper, a novel adaptive control scheme based on multiple parameter models is proposed to cope with a change in Parameters. Switching strategy guarantees the non-increase in the global control Lyapunov function if the estimation of Lyapunov function value converges. Least-square estimation is used to find the estimated value of the Lyapunov function. Switching and adaptation law guarantees the stability of closed-loop system in the sense of Lyapunov. Simulation results on anti-lock brake system are shown to verify the effectiveness of the proposed controller in view of a large change in system parameters.