• Structural Engineering and Mechanics
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• v.20 no.1
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• pp.85-110
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• 2005

This paper aims at formulating various statistical models for the study of a ten year Weigh-in-Motion (WIM) data collected from various WIM stations in Hong Kong. In order to study the bridge live load model it is important to determine the mathematical distributions of different load affecting parameters such as gross vehicle weights, axle weights, axle spacings, average daily number of trucks etc. Each of the above parameters is analyzed by various stochastic processes in order to obtain the mathematical distributions and the Maximum Likelihood Estimation (MLE) method is adopted to calculate the statistical parameters, expected values and standard deviations from the given samples of data. The Kolmogorov-Smirnov (K-S) method of approach is used to check the suitability of the statistical model selected for the particular parameter and the Monte Carlo method is used to simulate the distributions of maximum value stochastic processes of a series of given stochastic processes. Using the statistical analysis approach the maximum value of gross vehicle weight and axle weight in bridge design life has been determined and the distribution functions of these parameters are obtained under both free-flowing traffic and dense traffic status. The maximum value of bending moments and shears for wide range of simple spans are obtained by extrapolation. It has been observed that the obtained maximum values of the gross vehicle weight and axle weight from this study are very close to their legal limitations of Hong Kong which are 42 tonnes for gross weight and 10 tonnes for axle weight.

• Journal of the military operations research society of Korea
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• v.5 no.2
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• pp.15-25
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• 1979

Single-period inventory problems such as the newspaper boy problem having quadratic cost functions for both shortages and overage are examined to determine the optimal order level under various principles of choice such as minimum expected cost, aspiration level, and minimax regret. Procedures for finding the optimum order levels are developed for both continuous and discrete demand patterns.

• Journal of Mechanical Science and Technology
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• v.16 no.7
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• pp.959-965
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• 2002

Effective hydraulic conductivity of a statistically anisotropic heterogeneous medium is obtained for steady two-dimensional flows employing stochastic analysis. Flow equations are solved up to second order and the effective conductivity is obtained in a semi-analytic form depending only on the spatial correlation function and the anisotropy ratio of the hydraulic conductivity field, hence becoming a true intrinsic property independent of the flow field. Results are obtained using a statistically anisotropic Gaussian correlation function where the anisotropy is defined as the ratio of integral scales normal and parallel to the mean flow direction. Second order results indicate that the effective conductivity of an anisotropic medium is greater than that of an isotropic one when the anisotropy ratio is less than one and vice versa. It is also found that the effective conductivity has upper and lower bounds of the arithmetic and the harmonic mean conductivities.

• Journal of Korean Institute of Industrial Engineers
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• v.38 no.2
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• pp.89-97
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• 2012

This paper considers a manufacturer with a two-station make-to-stock and make-to-order serial production system. The MTS facility produces a single type of component and provides components for the MTO facility that produces customized products. In addition to the internal demand from the MTO facility, the MTS facility faces demands from the spot market with the option of to accept or reject each incoming demand. This paper addresses a joint component inventory rationing and batch production control which maximizes the manufacturer's profit. Using the Markov decision process model, we investigate the structural properties of the optimal inventory rationing and batch production policy, and present two types of heuristics. We implement a numerical experiment to compare the performance of the optimal and heuristic policies and a simulation study to examine the impact of the stochastic process variability on the inventory rationing and batch production control.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.65 no.4
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• pp.292-297
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• 2016

The first-order plus dead time(FOPDT) and second-order plus dead time(SOPDT), which describes a linear monotonic process quite well in most chemical and industrial processes and is often sufficient for PID and IMC controller tuning. This paper presents an application of heuristic harmony search(HS) optimization algorithm to the identification of linear continuous time-delay systems from step response. This recently developed HS algorithm is conceptualized using the musical process of searching for a perfect state of harmony. It uses a stochastic random search instead of a gradient search so that derivative information is unnecessary. The effectiveness of the proposed identification method has been demonstrated through a number of simulation examples.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.05a
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• pp.988-992
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• 2007

Recently, dynamic system has been enlarged and is exposed to various types of disturbance. Thus designing controller for those dynamic system under random disturbance is not practically easy. As a result, the exact analysis for the system which is exposed to various irregular disturbance is quite important. In order to perform analysis, conventional BMR(Balanced Model Reduction) method is applied to moment equation in stochastic domain and reliable reduced order system model has been obtained.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.742-745
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• 1994

In this paper we show the performance of neural Chandrasekhar filtering which is a special case for the new method of neural filtering using the artificial neural network systems developed recently for the filtering problems of linear and nonlinear, stationary and nonstationary stochastic signals. The neurofilter developed has either the finite impulse response(FIR) structure or the infinite impulse response(IIR) structure. The neurofilter differs from the conventional linear digital FIR and IIR filters because the artificial neural network system used in the neurofilter has nonlinear structure due to the sigmoid function. Numerical studies for the estimation of a second order Butterworth process are performed by changing the structures of the neurofilter in order to evaluate the performance indices under the changes of the output noises or disturbances. In the numerical studies both Chandrasekhar filtering estimates and true signals are used as the training signals for the neurofilter. The results obtained from the studies verified the capabilities which are essentially necessary for on-line filtering of various stochastic signals.

• Structural Engineering and Mechanics
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• v.8 no.5
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• pp.453-464
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• 1999

Safety monitoring systems of structures generally resort to detecting possible changes of dynamic system parameters. Sensitivity analysis of these dynamic system parameters may implement these techniques. Conventional structural eigenvalue problems are discussed in the scope of those systems with deterministic parameters. Large and flexible structures, such as suspension bridges, actually possess stochastic material properties and these random properties unavoidably affect the dynamic system parameters. The sensitivity matrix of structural modal parameters to basic design variables has been established in this paper. Moreover, second order statistics of natural frequencies due to the randomness of material properties have been discussed. It is concluded from numerical analysis of a modem suspension bridge that although the second order statistics of frequencies are small relatively to the change of basic design variables, such as density of mass and modulus of elasticity, the sensitivities of modal parameters to these variables at different locations change in magnitude.

• Journal of Korean Institute of Industrial Engineers
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• v.40 no.3
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• pp.313-320
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• 2014

We consider the problem to find economic inventory quantity of a single commodity under stochastic demands and order cancellation. In contrast to the traditional economic production quantity (EPQ) model, we assume that once the amount of inventory reaches to a predetermined level of quantity then the production is not halted but its production speed decreases until the inventory level drops to zero. We establish two probabilistic models representing the behaviors of both the high-production period and low-production period, respectively, and derive the relationship between the level of inventory and costs of production, cancellation, and holding, from which the quantity of economic inventory is obtained.

• Structural Engineering and Mechanics
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• v.31 no.5
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• pp.481-506
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• 2009

The present study is concerned with the stochastic linear free vibration study of laminated composite plate embedded with piezoelectric layers with random material properties. The system equations are derived using higher order shear deformation theory. The lamina material properties of the laminate are modeled as basic random variables for accurate prediction of the system behavior. A $C^0$ finite element is used for spatial descretization of the laminate. First order Taylor series based mean centered perturbation technique in conjunction with finite element method is outlined for the problem. The outlined probabilistic approach is used to obtain typical numerical results, i.e., the mean and standard deviation of natural frequency. Different combinations of simply supported, clamped and free boundary conditions are considered. The effect of side to thickness ratio, aspect ratio, lamination scheme on scattering of natural frequency is studied. The results are compared with those available in literature and an independent Monte Carlo simulation.