• Structural Engineering and Mechanics
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• 제56권6호
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• pp.959-982
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• 2015

In this study, a non-stationary random earthquake Clough-Penzien model is used to describe earthquake ground motion. Using stochastic direct integration in combination with an equivalent linear method, a solution is established to describe the non-stationary response of lead-rubber bearing (LRB) system to a stochastic earthquake. Two parameters are used to develop an optimization method for bearing design: the post-yielding stiffness and the normalized yield strength of the isolation bearing. Using the minimization of the maximum energy response level of the upper structure subjected to an earthquake as an objective function, and with the constraints that the bearing failure probability is no more than 5% and the second shape factor of the bearing is less than 5, a calculation method for the two optimal design parameters is presented. In this optimization process, the radial basis function (RBF) response surface was applied, instead of the implicit objective function and constraints, and a sequential quadratic programming (SQP) algorithm was used to solve the optimization problems. By considering the uncertainties of the structural parameters and seismic ground motion input parameters for the optimization of the bearing design, convex set models (such as the interval model and ellipsoidal model) are used to describe the uncertainty parameters. Subsequently, the optimal bearing design parameters were expanded at their median values into first-order Taylor series expansions, and then, the Lagrange multipliers method was used to determine the upper and lower boundaries of the parameters. Moreover, using a calculation example, the impacts of site soil parameters, such as input peak ground acceleration, bearing diameter and rubber shore hardness on the optimization parameters, are investigated.

• Wind and Structures
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• 제20권6호
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• pp.763-791
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• 2015

"Wind and Ports" is a European project that has been carried out since 2009 to handle wind forecast in port areas through an integrated system made up of an extensive in-situ wind monitoring network, the numerical simulation of wind fields, the statistical analysis of wind climate, and algorithms for medium-term (1-3 days) and short term (0.5-2 hours) wind forecasting. The in-situ wind monitoring network, currently made up of 22 ultrasonic anemometers, provides a unique opportunity for detecting high resolution thunderstorm records and studying their dominant characteristics relevant to wind engineering with special concern for wind actions on structures. In such a framework, the wind velocity of thunderstorms is firstly decomposed into the sum of a slowly-varying mean part plus a residual fluctuation dealt with as a non-stationary random process. The fluctuation, in turn, is expressed as the product of its slowly-varying standard deviation by a reduced turbulence component dealt with as a rapidly-varying stationary Gaussian random process with zero mean and unit standard deviation. The extraction of the mean part of the wind velocity is carried out through a moving average filter, and the effect of the moving average period on the statistical properties of the decomposed signals is evaluated. Among other aspects, special attention is given to the thunderstorm duration, the turbulence intensity, the power spectral density and the integral length scale. Some noteworthy wind velocity ratios that play a crucial role in the thunderstorm loading and response of structures are also analyzed.

• 응용통계연구
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• 제23권5호
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• pp.909-921
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• 2010

패널 자료에서 무응답이 발생한 경우에는 횡시점회귀대체법(cross-wave regression imputation) 등과 같은 대체법을 이용하여 무응답 문제를 해결한다. 최근 표본 틀(sampling frame) 자료를 이용하여 무응답 가중치 보정을 하는 BLS 무응답 보정법은 패널 자료에도 적용 가능한 방법으로 알려져있다. 본 논문에서는 패널자료에서 BLS 무응답 보정법을 이용한 대체법을 연구하였으며 자료가 경향이 있는 비정상시계열(nonstationary process with drift)을 따른 다는 조건하에서 BLS 무응답 보정법과 횡시점회귀대체법의 하나인 이월대체법(carry-over imputation)과의 이론적 관계를 살펴보았다. 모의실험을 통하여 이론적인 결과를 확인하였으며, 2007년 매월노동통계 자료를 이용하여 두 방법의 우수성을 비교하였다.

• 동력기계공학회지
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• 제4권2호
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• pp.40-45
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• 2000

Some engineering materials are often known to have considerable spatial variation in their resisting strength and other properties. The objective of this study is to investigate the averaging effect and the applicability of extremal statistic for the statistical size effect. In the present study, it is assumed that the material property is a stationary random process in space. The theoretical autocorrelation function of the material strength are discussed for several correlation lengths. And, in order to investigate the statistical size effect, the material properties was simulated by using the non-Gaussian random process method. The material properties were plotted on the Weibull probability papers. The main results are summarized as follows: The autocorrelation function of the material properties are almost independent of the averaging length. The variance decreases with increasing the averaging length. As correlation length is smaller, the slope is larger. And also, it was found that Weibull statistics based on the weakest-link model could not explain the spatial variation of material properties with respect to the size effect satisfactory.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 학술대회 논문집 정보 및 제어부문
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• pp.159-161
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• 2004

Many motion object detection algorithms rely on the process of background subtraction, an important technique that is used for detecting changes from a model of the background scene. This paper propose a novel method to update the background model image of a visual surveillance system which is not stationary. In order to do this, we use a background model based on statistical qualities of monitored images and another background model that excluded motions. By comparing each changed area computed from the two background model images and current monitored image, the areas that will be updated are decided.

• 대한수학회지
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• 제55권1호
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• pp.147-160
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• 2018

In this article, we establish translation theorems for the analytic Fourier-Feynman transform of functionals in non-stationary Gaussian processes on Wiener space. We then proceed to show that these general translation theorems can be applied to two well-known classes of functionals; namely, the Banach algebra S introduced by Cameron and Storvick, and the space ${\mathcal{B}}^{(P)}_{\mathcal{A}}$ consisting of functionals of the form $F(x)=f({\langle}{\alpha}_1,x{\rangle},{\ldots},{\langle}{\alpha}_n,x{\rangle})$, where ${\langle}{\alpha},x{\rangle}$ denotes the Paley-Wiener-Zygmund stochastic integral ${\int_{0}^{T}}{\alpha}(t)dx(t)$.

• Structural Engineering and Mechanics
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• 제25권1호
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• pp.21-37
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• 2007

In this study a stochastic approach for linear viscous dampers design adopted for seismic protection of buildings is developed. Devices optimal placement into the main structure and their mechanical parameters are attained by means of a reliability-based optimum design criterion, in which an objective function (O.F.) is minimized, subject to a stochastic constraint. The seismic input is modelled by a non stationary modulated Kanai Tajimi filtered stochastic process. Building is represented by means of a plane shear type frame model. The selected criterion for the optimization searches the minimum of the O.F., here assumed to be the cost of the seismic protection, i.e., assumed proportional to the sum of added dampings of each device. The stochastic constraint limits a suitable approximated measure of the structure failure probability, here associated to the maximum interstorey drift crossing over a given threshold limit, related, according with modern Technical Codes, to the required damage control.

• Journal of information and communication convergence engineering
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• 제6권3호
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• pp.337-342
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• 2008

Controlling spillway gates of dams is a complex, nonlinear, non-stationary control process and is significantly affected by hydrological conditions which are not predictable beforehand. In this paper, control methods based on dynamic fuzzy control are proposed for the operation of spillway gates of dams during floods. The proposed methods are not only suitable for controlling spillway gates but also able to maintain target water level in order to prepare a draught. In the proposed methods, we use dynamic fuzzy control that the membership functions can be varied by changing environment conditions for keeping up the target water level, instead of conventional static fuzzy control. Simulation results demonstrate that the proposed methods based on dynamic fuzzy control produce an accurate and efficient solution for both of controlling spillway gates and maintaining target water level defined beforehand.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1996년도 추계학술대회 논문집
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• pp.248-254
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• 1996

A disturbance rejection controller using eccentricity filtering and LQ control techniques is proposed to alleviate significantly the effect of roll eccentricity in multivariable cold-rolling processes. Fundamental problems such as process time delay inherent in exit thickness measurement and non-stationary characteristics of roll eccentricity signals can be overcome by the proposed control method. The filtered instantaneous estimate of roll eccentricity may be exploited to improve instantaneous estimate of the exit thickness variation based on roll force and roll gap mearsurements, and a feedforward compensator is augmented as a reference for a gaugemeter thickness estimator. And, LQ feedback controller is combined with eccentricity filter for the attenuation of the exit thickness variation due to the entry thickness variation. The simulation results show that eccentricity components have been significantly eliminated and simultaneously other distrubances also have been attenuated.

• 상하수도학회지
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• 제12권4호
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• pp.43-52
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• 1998

The purpose of this study is to establish a method of estimating the daily urban water demend using Backpropagation algorithm is part of ANN(Artificial Neural Network). This method will be used for the development of the efficient management and operations of the water supply facilities. The data used were the daily urban water demend, the population and weather conditions such as treperarture, precipitation, relative humidity, etc. Kwangju city was selected for the case study area. We adjusted the weights of ANN that are iterated the training data patterns. We normalized the non-stationary time series data [-1,+1] to fast converge, and choose the input patterns by statistical methods. We separated the training and checking patterns form input date patterns. The performance of ANN is compared with multiple-regression method. We discussed the representation ability the model building process and the applicability of ANN approach for the daily water demand. ANN provided the reasonable results for time series forecasting.