• Journal of Korean Society of Industrial and Systems Engineering
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• v.28 no.3
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• pp.36-41
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• 2005

페트리 네트(Petri Nets)는 이산 사건 시스템을 모델링할 수 있는 그래픽하고, 수학적인 도구이다. 본 연구는 유연제조 시스템을 확률적인 페트리 네트(Stochastic Petri Nets)중의 하나인 임베디드 마코프 체인(Embeded Markov Chain)에 도입하고, 임베디드 마코프 체인의 방법 중에 하나인 일반화된 확률적 페트리 네트(Generalized Stochastic Perti Nets)에 적용시켰다. 그리고 결과치의 정확성을 알아내기 위하여, 페트리 네트 시뮬레이션과 아레나를 사용하여 실행하였다.

• Journal of the Korean Mathematical Society
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• v.59 no.2
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• pp.279-298
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• 2022

In this paper, the existence and uniqueness for the global solution of neutral stochastic functional differential equation is investigated under the locally Lipschitz condition and the contractive condition. The implicit iterative methodology and the Lyapunov-Razumikhin theorem are used. The stability analysis for such equations is also applied. One numerical example is provided to illustrate the effectiveness of the theoretical results obtained.

• Nonlinear Functional Analysis and Applications
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• v.27 no.4
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• pp.813-837
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• 2022

In this paper we consider inverse problem for a general class of nonlinear stochastic differential equations on Hilbert spaces whose generating operators (drift, diffusion and jump kernels) are unknown. We introduce a class of function spaces and put a suitable topology on such spaces and prove existence of optimal generating operators from these spaces. We present also necessary conditions of optimality including an algorithm and its convergence whereby one can construct the optimal generators (drift, diffusion and jump kernel).

• Nonlinear Functional Analysis and Applications
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• v.28 no.2
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• pp.365-382
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• 2023

In this paper we prove the existence and uniqueness of solution of stochastic fractional neutral differential equations with Gaussian noise or Lévy noise by using the Picard-Lindelöf successive approximation scheme. Further stability results of nonlinear stochastic fractional dynamical system with Gaussian and Lévy noises are established. Examples are provided to illustrate the theoretical results.

• Geotechnical Engineering
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• v.4 no.3
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• pp.19-26
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• 1988

A stochastic numerical model for predictions of differential settlement of foundation Eoils is developed in this Paper. The differential settlement is highly dependent on the spatial variability of elastic modulus of soil. The Kriging method is used to account for the spatial variability of the elastic modulus. This technique provides the best linear unbiased estimator of a parameter and its minimum variance from a limited number of measured data. The stochastic finite element method, employing the first-order second-moment analysis for computations of error Propagation, is used to obtain the means, ariances, and covariances of nodal displacements. Finally, a reliability model of differential settlement is proposed by using the results of the stochastic FEM analysis. It is found that maximum differential settlement occurs when the distance between two foundations is approximately same It with the scale of fluctuation in horizontal direction, and the probability that differential settlement exceeds the allot.able vague might be significant.

• Structural Engineering and Mechanics
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• v.28 no.4
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• pp.373-386
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• 2008

In this study stochastic analysis of non-linear dynamical systems under ${\alpha}$-stable, multiplicative white noise has been conducted. The analysis has dealt with a special class of ${\alpha}$-stable stochastic processes namely sub-Gaussian white noises. In this setting the governing equation either of the probability density function or of the characteristic function of the dynamical response may be obtained considering the dynamical system forced by a Gaussian white noise with an uncertain factor with ${\alpha}/2$- stable distribution. This consideration yields the probability density function or the characteristic function of the response by means of a simple integral involving the probability density function of the system under Gaussian white noise and the probability density function of the ${\alpha}/2$-stable random parameter. Some numerical applications have been reported assessing the reliability of the proposed formulation. Moreover a proper way to perform digital simulation of the sub-Gaussian ${\alpha}$-stable random process preventing dynamical systems from numerical overflows has been reported and discussed in detail.

• Advances in materials Research
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• v.13 no.4
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• pp.299-319
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• 2024

Due to higher strength-to-weight ratio of composite laminates, they find uses in many weight-sensitive applications like aerospace, automobile and marine structures. From a reliability point of view, accurate prediction of failure of these structures is important. Due to the complexities in the manufacturing processes of composite laminates, there is a variation in the material properties and geometric parameters. Hence stochastic aspects are important while designing the composite laminates. Many existing works of composite laminate failure analysis are based on the deterministic approach but it is important to consider the randomness in the material properties, geometry and loading to predict accurate failure loads. In this paper the statistics of the ultimate failure load of the [0/θ]_s laminated composite plate (LCP) containing the edge crack and voids subjected to the tensile loading are presented in terms of the mean and coefficient of variance (COV). The objective is to better the efficacy of laminate failure by predicting the statistics of the ultimate failure load of LCP with random material, geometric and loading parameters. The stochastic analysis is done by using the extended finite element method (XFEM) combined with the second-order perturbation technique (SOPT). The ultimate failure load of the LCP is obtained by ply-by-ply failure analysis using the ply discount method combined with the Tsai-Wu failure criterion. The aim is to know the effect of the stacking sequence, crack length, crack angle, location of voids and number of voids on the mean and corresponding COV of the ultimate failure load of LCP is investigated. The results of the ultimate failure load obtained by the present method are in good agreement with the existing experimental and numerical results. It is observed that [0/θ]_s LCPs are very sensitive to the randomness in the crack length, applied load, transverse tensile strength of the laminate and modulus of elasticity of the material, so precise control of these parameters is important. The novelty of the present study is, the stochastic implementation in XFEM for the failure prediction of LCPs containing crack and voids.

• Journal of The Korean Society of Agricultural Engineers
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• v.55 no.3
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• pp.75-84
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• 2013

The seepage quantity analysis of reservoir embankment is very important for assessment of embankment safety. However, the conventional analysis does not consider uncertainty of soil properties. Permeability is known that the coefficient of variation is larger than other soil properties and seepage quantity is highly dependent on the permeability of embankment. Therefore, probabilistic analysis should be carried out for seepage analysis. To designers, however, the probabilistic analysis is not an easy task. In this paper, the method that can be performed probabilistic analysis easily and efficiently through the numerical analysis based commercial program is proposed. Stochastic response surface method is used for approximate the limit state function and when estimating the coefficients, the moving least squares method is applied in order to reduce local error. The probabilistic analysis is performed by LHC-MCS through the response surface. This method was applied to two type (homogeneous, core zone) earth dams and permeability of embankment body and core are considered as random variables. As a result, seepage quantity was predicted effectively by response surface and probabilistic analysis could be successfully implemented.

• Advances in aircraft and spacecraft science
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• v.7 no.5
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• pp.405-423
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• 2020

Non-linear energy sink (NES) is an emerging passive absorber able to mitigate the dynamic response of structures without any external energy supply, resonating with all the modes of the primary structure to control. However, its inherent non-linearities hinder its large-scale use and leads to complicated design procedures. For this purpose, an approximate design approach is herein proposed in a stochastic framework. Since loads are random in nature, the stochastic analysis of non-linear systems may be performed by means of computational intensive techniques such as Monte Carlo simulations (MCS). Alternatively, the Stochastic Linearisation (SL) technique has proven to be an effective tool to investigate the performance of different passive control systems under random loads. Since controlled systems are generally non-classically damped and most of SL algorithms operate recursively, the computational burden required is still large for those problems that make intensive use of SL technique, as optimal design procedures. Herein, a procedure to speed up the Stochastic Linearisation technique is proposed by avoiding or strongly reducing numerical evaluations of response statistics. The ability of the proposed procedure to effectively reduce the computational effort and to reliably design the NES is showed through an application on a well-known case study related to the vibrations mitigation of an aircraft wing.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.12
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• pp.2828-2835
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• 2015

In this paper, we analyse the effect of redundancy types and non-stop forwarding scheme on network service availability. We use stochastic reward net models as enabling modeling approach for the analytical evaluation. We first design stochastic reward nets for redundancy models with or without non-stop forwarding and then evaluate their availability using Stochastic Petri Net Package.