• 전산구조공학
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• 제5권1호
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• pp.97-108
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• 1992

이 논문에서는 구조시스템신뢰성해석에 있어서 부재의 파괴후 잔류강도의 불확실성을 고려하였다. 이를 위하여 확율유한요소법(Stochastic Finite Element Method: SFEM)을 시스템신뢰성해석과정에 접합하였다. 확율유한요소법은 신뢰성해석시 재료와 기하학적 변수의 불확실성을 좀더 함축적으로 고려할 수 있는 것으로 알려져 있으며, 본 논문에서 이 방법을 구조부재와 구조시스템의 신뢰성해석에 적용해 보았다. 이 논문의 방법과 파괴된 부재의 잔류응력을 확정적으로 취급하는 방법과 그 결과를 비교하였으며, 부재가 파괴된 후 그 잔류강도의 불확실성이 구조시스템 신뢰성에 주는 영향을 보기위해 여러 경우를 고찰해 보았다. 그 결과로부터 부재의 파괴 후 잔류강도가 구조시스템신뢰성에 대단히 큰 영향을 준다는 것을 다시 확인할 수 있었다. 이 논문의 여러경우에 대한 연구로 부터 좀 더 나은 구조시스템신뢰성의 평가를 위해서 부재의 파괴후 거동이 갖는 불확실성을 구조시스템신뢰성해석시, 특히 부재의 파괴후 거동이 semi-brittle인 경우에, 고려해야 한다는 결론을 내릴 수 있겠다. 이점을 받아들인다면 확율유한요소법이 구조시스템신뢰성해석에 있어서 적합한 방법일 것이다.

• 응용통계연구
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• 제26권3호
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• pp.413-420
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• 2013

확률적 날씨 발생기(Stochastic weather generator)는 일일 날씨를 생성하는데 일반적으로 사용되는 방법으로 최근에는 일반화선형모형에 기초한 확률적 날씨 발생 방법이 제안되었다. 본 논문에서는 서울지역의 일일 기온을 모형화하하기 위해서 일반화선형모형에 기초한 확률적 날씨 발생기를 고려하였다. 이 모형에서는 계절성을 나타내는 변수와 강우발생 유무가 공변수로 사용되었다. 일반적으로 확률적 날씨 발생기에서는 생성된 일일 날씨가 월별 또는 계절별 총강우량이나 평균온도에 충분한 변동을 만들어 내지 못하는 과대산포 현상이 발생하는데, 이러한 한계를 극복하기 위해 본 연구에서는 평활된 계절별 평균 온도를 일반화선형모형의 공변수로 추가하였다. 그리고 제안된 모형을 1961년부터 2011년까지 51년 동안의 서울지역 일일 평균 기온자료에 적용하였다.

• 한국시뮬레이션학회:학술대회논문집
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• 한국시뮬레이션학회 1994년도 추계학술발표회 및 정기총회
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• pp.1-2
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• 1994

With the prevalence of computers in modern organizations, simulation is receiving more atention as an effectvie decision -making tool. Simualtion is a computer-based numerical technique which uses mathmatical and logical models to approximate the behaviror of a real-world system. However, iptimization of synamic stochastic systems often defy analytical and algorithmic soluions. Although a simulation approach is often free fo the liminting assumption s of mathematical modeling, cost and time consiceration s make simulation the henayst's last resort. Therefore, whenever possible, analytical and algorithmica solutions are favored over simulation. This paper discussed the issues and procedrues for using simulation as a tool for optimization of stochastic complex systems that are dmodeled by computer simulation . Its emphasis is mostly on issues that are speicific to simulation optimization instead of consentrating on the general optimizationand mathematical programming techniques . A simulation optimization problem is an optimization problem where the objective function. constraints, or both are response that can only be evauated by computer simulation. As such, these functions are only implicit functions of decision parameters of the system, and often stochastic in nature as well. Most of optimization techniqes can be classified as single or multiple-resoneses techniques . The optimization of single response functins has been researched extensively and consists of many techniques. In the single response category, these strategies are gradient based search techniques, stochastic approximate techniques, response surface techniques, and heuristic search techniques. In the multiple response categroy, there are basically five distinct strategies for treating the responses and finding the optimum solution. These strategies are graphica techniqes, direct search techniques, constrained optimization techniques, unconstrained optimization techniques, and goal programming techniques. The choice of theprocedreu to employ in simulation optimization depends on the analyst and the problem to be solved. For many practival and industrial optimization problems where some or all of the system components are stochastic, the objective functions cannot be represented analytically. Therefore, modeling by computersimulation is one of the most effective means of studying such complex systems. In this paper, after discussion of simulation optmization techniques, the applications of above techniques will be presented in the modeling process of many flexible manufacturing systems.

• Structural Engineering and Mechanics
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• 제80권6호
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• pp.645-655
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• 2021

Performance-based reliability analysis is a practical approach to investigate the seismic performance and stochastic nonlinear response of structures considering a random process. This is significant due to the uncertainties involved in every aspect of the analysis. Therefore, the present study aims to evaluate the performance-based reliability within a stochastic finite element (FE) framework for reinforced concrete (RC) shear walls that are considered as one of the most essential elements of structures. To accomplish this purpose, deterministic FE analyses are conducted for both squat and slender shear walls to validate numerical models through experimental results. The presented numerical analysis is performed by using the ABAQUS FE program. Afterwards, a random-effects investigation is carried out to consider the influence of different random variables on the lateral load-top displacement behavior of RC members. Using these results and through utilizing the Monte-Carlo simulation method, stochastic nonlinear analyses are also performed to generate random FE models based on input parameters and their probabilistic distributions. In order to evaluate the reliability of RC walls, failure probabilities and corresponding reliability indices are calculated at life safety and collapse prevention levels of performance as suggested by FEMA 356. Moreover, based on reliability indices, capacity reduction factors are determined subjected to shear for all specimens that are designed according to the ACI 318 Building Code. Obtained results show that the lateral load and the compressive strength of concrete have the highest effects on load-displacement responses compared to those of other random variables. It is also found that the probability of shear failure for the squat wall is slightly lower than that for slender walls. This implies that 𝛽 values are higher in a non-ductile mode of failure. Besides, the reliability of both squat and slender shear walls does not change significantly in the case of varying capacity reduction factors.

• Advances in materials Research
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• 제13권4호
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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.

• 한국통신학회논문지
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• 제31권7A호
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• pp.649-658
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• 2006

최근 소프트웨어 개발은 client/server 시스템이나 웹 프로그래밍, 객체지향 개발, 네트워크 환경에 의한 분산개발 등 새로운 개발 형태로써 다양하게 적용되고 있다. 한편 소프트웨어 분산 개발에 대한 기술도 관심이 되고 있으며, 객체지향 개념이 확대되고 있다. 이러한 기술에 의한 개발 작업량의 대폭 삭감이나 소프트웨어 품질 및 생산 개선의 효과가 점차 증대되어 가는 추세로 향후 광범위한 분야에 분산된 다수의 워크스테이션에 의해 병행되어 개발된 객체(object)를 이용한 분산개발의 발전에 대해 고찰한다. 본 논문에서는 이러한 분산 소프트웨어 개발환경을 대상으로 확률미분방정식 모델에 의한 소프트웨어 최척 배포문제를 논한다. 과거에는 소프트웨어 개발 프로세스에 의한 출하 품질의 파악이나 시험 진도관리에 의한 신뢰성 평가를 행하는 접근방법(approach)에 의해 소프트웨어의 고장 발생 현상을 불확정 사상에 의해 확률, 통계적으로 취급하는 방법을 적용하였으나 본고에서는 fault 발견과정에서 계수에 의해 취급되는 비동차포아송과정(NHIPP: Non-Homogeneous Poisson Process) 에 의한 SRGM과 fault 발견 과정을 연속적으로 변동하는 확률 과정의 모델화된 확률 미분방정식 (SDE: stochastic differential equation)에 의한 SRGM을 제안하여 최적의 배포시기를 결정한다. 여기서 시험단계 및 운용단계에 발생하는 비용 요인으로부터 도출된 총 소프트웨어 비용을 최소로 하는 시험시간인 최적 배포시기를 구한다. 특히, 총 소프트웨어 비용의 확률분포를 고려하여 최적 배포시기의 신뢰 한계도 논한다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1986년도 하계학술대회논문집
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• pp.274-277
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• 1986

• 한국전산유체공학회:학술대회논문집
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• 한국전산유체공학회 2008년도 12th Asian Congress of Fluid Mechanics
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• pp.57.4-58
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• 2008

• 충청수학회지
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• 제31권1호
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• pp.65-73
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• 2018

We investigate the optimal consumption and investment problem of working agent who faces tax system on consumption, labor income, savings and investment. By applying martingale method, we obtain the closed-form solutions so it is possible to verify the effect of tax system analytically.

• 한국경영과학회지
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• 제35권2호
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• pp.19-35
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• 2010

Many papers have used a two-stage approach of first calculating DEA efficiency scores and then seeking to correlate these scores with various environmental variables. Most of the studies have not checked whether such a two-stage approach is statistically valid for identifying significant environmental variables. Recently Simar and Wilson (2007) (SW) introduce a sensible data generating process and bootstrap procedure based on truncated regression for the two-stage approach. Banker and Natarajan (2008) (BN) provide a statistical foundation for the two-stage approach comprising a DEA followed by an ordinary least squares or maximum likelihood estimation. Researchers have to identify an approach suitable for their research circumstances in terms of properties, merits, demerits, and robustness to plausible departures from its chosen data generating process. We summarize the foundations and properties of the two-stage procedures suggested by SW and BN. And we discuss merits and demerits of those procedures. Also using Monte Carlo simulation we assess their relative performance under several misspecified settings.