• 한국지반공학회:학술대회논문집
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• 한국지반공학회 2002년도 봄 학술발표회 논문집
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• pp.651-656
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• 2002

In general, the most important problem in slope stability analysis is that there is no definite way to describe the natural three-dimensional Joint network. Therefore, the many approaches were tried to anlayze the slope stability. Numerical modeling approach is one of the branch to resolve the complexity of natural system. UDEC, FLAC, and SWEDGE are widely used commercial code for the purpose on stability analysis. For the purpose on the more appropriate application of these kind of code, however, three-dimensional distribution of joint network must be identified in more explicit way. Remaining problem is to definitely describe the three dimensional network of joint and bedding, but it is almost impossible in practical sense. Three dimensional joint generation method with random number generation and the results of generation to UDEC have been applied to settle the refered problems in field site. However, this approach also has a important problem, and it is that joint network is generated only once. This problem lead to the limitation on the application to field case, in practical sense. To get rid of this limitation, Monte Carlo Simulation is proposed in this study 1) statistical analysis of input values and definition of the applied system with statistical parameter, 2) instead of the consideration of generated network as a real system, generated system is just taken as one reliable system, 3) present the design parameters, through the statistical analysis of ouput values Results of this study are not only the probability of failure, but also area of failure block, shear strength, normal strength and failure pattern, and all of these results are described in statistical parameters. The results of this study, shear strength, failure area, pattern etc, can provide the direct basement on the design, cutoff angle, support pattern, support strength and etc.

• 한국정보통신학회논문지
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• 제17권9호
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• pp.2227-2232
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• 2013

유도제어 시스템 체계개발의 초기단계에는 운용 효과도 도출 및 요구사항 적합성 검토를 통한 체계 개략사양도출을 위해 효과도 분석을 수행한다. 본 논문의 목표는 M&S (Modeling & Simulation)를 활용한 운용 효과도 분석을 통해 고속 무인 수중운동체의 목표점 도달 임무를 위한 체계 요구사항 도출이다. 운용 효과도는 대상 수중운동체의 목표점 도달 정확도로 정의한다. 도달 정확도에 가장 큰 영향을 미칠 것으로 예상되는 변수는 항법센서 성능이다. 본 논문에서는 관성항법센서(Inertial Navigation Sensor, INS)와 도플러 속도 측정 장치(Doppler Velocity Log, DVL)를 이용한 복합항법을 고려하였다. 몬테카를로 수치 시뮬레이션을 통해 항법센서 성능에 대한 효과도 분석을 수행한다. 몬테카를로 수치 시뮬레이션 결과는 CEP(Circular Error Probability)와 분산을 이용한 확률분석을 통해 분석한다. 상용 항법센서 가격을 고려하여 최적의 가격대 성능비를 갖는 항법센서 성능을 제시한다.

• Nuclear Engineering and Technology
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• 제56권5호
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• pp.1747-1753
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• 2024

The accurate determination of formation density and the physical properties of rocks is the most critical logging tasks which can be obtained using gamma-ray transport and detection tools. Though the simulation works published so far have considerably improved the knowledge of the parameters that govern the responses of the detectors in these tools, recent studies have found considerable differences between the results of using a conventional model of a homogeneous mixture of formation and fluid and an inhomogeneous fractured medium. It has increased concerns about the importance of the complexity of the model used for the medium in simulation works. In the present study, we have suggested two various models for the flow of the fluid in porous media and fractured rock to be used for logging purposes. For a typical gamma-gamma logging tool containing a ¹³⁷Cs source and two NaI detectors, simulated by using the MCNPX code, a simplified porous (SP) model in which the formation is filled with elongated rectangular cubes loaded with either mineral material or oil was investigated. In this model, the oil directly reaches the top of the medium and the connection between the pores is not guaranteed. In the other model, the medium is a large 3-D matrix of 1 cm³ randomly filled cubes. The designed algorithm to fill the matrix sites is so that this realistic random (RR) model provides the continuum growth of oil flow in various disordered directions and, therefore, fulfills the concerns about modeling the rock textures consist of extremely complex pore structures. For an arbitrary set of oil concentrations and various formation materials, the response of the detectors in the logging tool has been considered as a criterion to assess the effect of modeling for the distribution of pores in the formation on simulation studies. The results show that defining a RR model for describing heterogeneities of a porous medium does not effectively improve the prediction of the responses of logging tools. Taking into account the computational cost of the particle transport in the complex geometries in the Monte Carlo method, the SP model can be satisfactory for gamma-gamma logging purposes.

• 센서학회지
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• 제25권4호
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• pp.264-270
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• 2016

Self-powered neutron detector (SPND) is a sensor to monitor a neutron flux proportional to a reactor power of the nuclear power plants. Since an SPND is usually installed in the reactor core and does not require additional outside power, it generates electrons itself from interaction between neutrons and a neutron-sensitive material called an emitter, such as rhodium and vanadium. This paper presents the simulations of the depletion sensitivity evaluations based on MCNP models of rhodium and vanadium SPNDs and light water reactor fuel assembly. The evaluations include the detail geometries of the detectors and fuel assembly, and the modeling of rhodium and vanadium emitter depletion using MCNP and ORIGEN-S codes, and the realistic energy spectrum of beta rays using BETA-S code. The results of the simulations show that the lifetime of an SPND can be prolonged by using vanadium SPND than rhodium SPND. Also, the methods presented here can be used to analyze a life-time of those SPNDs using various emitter materials.

• 한국신뢰성학회지:신뢰성응용연구
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• 제18권1호
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• pp.33-39
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• 2018

Purpose: Accelerated degradation tests can be effective in assessing product reliability when degradation leading to failure can be observed. This article proposes an accelerated degradation test model for highly reliable solid state drives (SSDs). Methods: We suggest a nonlinear mixed-effects (NLME) model to degradation data for SSDs. A Monte Carlo simulation is used to estimate lifetime distribution in accelerated degradation testing data. This simulation is performed by generating random samples from the assumed NLME model. Conclusion: We apply the proposed method to degradation data collected from SSDs. The derived power model is shown to be much better at fitting the degradation data than other existing models. Finally, the Monte Carlo simulation based on the NLME model provides reasonable results in lifetime estimation.

• 전자공학회논문지D
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• 제34D권5호
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• pp.32-44
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• 1997

A three-dimensional (3D) full-dynamic damage model for ion implantation in crystalline silicon was proposed to calculate more accurately point defect distributions and ion-implanted concentration profiles during ion implantation process. The developed model was based on the physical monte carlo approach. This model was applied to simulate B and BF2 implantation. We compared our results for damage distributions with those of the analytical kinchin-pease approach. In our result, the point defect distributions obtained by our new model are less than those of kinchin-pease approach, and the vacancy distributions differ from the interstitial distributions. The vacancy concentrations are higher than the interstitial ones before 0.8 . Rp to the silicon surface, and after the 0.8 . Rp to the silicon bulk, the interstitial concentrations are revesrsely higher than the vacancy ones.The fully-dynamic damage model for the accumulative damage during ion implantation follows all of the trajectories of both ions and recoiled silicons and, concurrently, the cumulative damage effect on the ions and the recoiled silicons are considered dynamically by introducing the distributon probability of the point defect. In addition, the self-annealing effect of the vacancy-interstitial recombination during ion implantation at room temperature is considered, which resulted in the saturation level for the damage distribution.

• 대한기계학회논문집B
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• 제30권1호
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• pp.1-7
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• 2006

The characteristics of micro gaseous flows in microchannels have been analyzed in view of flow resistance using the direct simulation Monte Carlo (DSMC) method which is a molecule-based numerical modeling technique. For this purpose, a DSMC code where the pressure boundary condition was specified at the inlet and outlet, has been developed and the results of simulations showed satisfactory agreements with the analytic solution in the slip flow regime. (0.01 < Kn < 0.1) By varying the height and length of the microchannel, the effect of pressure difference between the inlet and outlet was examined. The present computation indicates that the curvature in pressure distribution along the channel increases due to the effect of compressibility when the pressure difference increases. To obtain the flow resistance regardless of the channel dimensions, a standard curve is devised in the present study by introducing the concept of unit mass flowrate and unit driving pressure force. From this curve, it is shown that in micro flows, a significant deviation from the laminar incompressible flow occurs by reducing the flow resistance.

• Wind and Structures
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• 제27권3호
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• pp.175-186
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• 2018

With the continuous increase of span lengths, modern bridges are becoming much more flexible and more prone to flutter under wind excitations. A reasonable probabilistic flutter analysis of long-span bridges involving random and uncertain variables may have to be taken into consideration. This paper presents a method for estimating the reliability index and failure probability due to flutter, which considers the very important variables including the extreme wind velocity at bridge site, damping ratio, mathematical modeling, and flutter derivatives. The Aizhai Bridge in China is selected as an example to demonstrate the numerical procedure for the flutter reliability analysis. In the presented method, the joint probability density function of wind speed and wind direction at the deck level of the bridge is first established. Then, based on the fundamental theories of structural reliability, the reliability index and failure probability due to flutter of the Aizhai Bridge is investigated by applying the Monte Carlo method and the first order reliability method (FORM). The probabilistic flutter analysis can provide a guideline in the design of long-span bridges and the results show that the structural damping and flutter derivatives have significant effects on the flutter reliability, more accurate and reliable data of which is needed.

• 한국인터넷방송통신학회논문지
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• 제17권1호
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• pp.107-113
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• 2017

이 논문은 벡터 양자기가 포함된 부대역 코덱의 분석과 설계에서 벡터 양자기를 모델링하는 새로운 방법을 제시해준다. 우리는 각 코드북의 시작점들의 수(N), 각 코드워드의 길이(k), 필터 대역 계수들에 의존하는 부대역 코덱 시스템의 입력과 출력의 평균자승 회복 오차(MSE)를 계산한다. 본 논문은 확률밀도함수로 최적화된 벡터양자기가 존재하는 최적의 M밴드 필터 뱅크 구조는 등가의 스칼라 양자기의 변수들의 적절한 선택으로 구현될 수 있음을 보였다. 특정한 구현 예를 두 개의 다른 필터뱅크 구조인 Paraunitary 필터 뱅크와 Biorthogonal 필터 뱅크를 2채널 경우에 개발하였다. 이 이론적인 결과들은 확장의 Monte Carlo 시뮬레이션으로 확인되었다.

• Smart Structures and Systems
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• 제21권5호
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• pp.601-609
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• 2018

The estimated probabilistic model of wind data based on the conventional approach may have high discrepancy compared with the true distribution because of the uncertainty caused by the instrument error and limited monitoring data. A sequential quadratic programming (SQP) algorithm-based finite mixture modeling method has been developed in the companion paper and is conducted to formulate the joint probability density function (PDF) of wind speed and direction using the wind monitoring data of the investigated bridge. The established bivariate model of wind speed and direction only represents the features of available wind monitoring data. To characterize the stochastic properties of the wind parameters with the subsequent wind monitoring data, in this study, Bayesian inference approach considering the uncertainty is proposed to update the wind parameters in the bivariate probabilistic model. The slice sampling algorithm of Markov chain Monte Carlo (MCMC) method is applied to establish the multi-dimensional and complex posterior distribution which is analytically intractable. The numerical simulation examples for univariate and bivariate models are carried out to verify the effectiveness of the proposed method. In addition, the proposed Bayesian inference approach is used to update and optimize the parameters in the bivariate model using the wind monitoring data from the investigated bridge. The results indicate that the proposed Bayesian inference approach is feasible and can be employed to predict the bivariate distribution of wind speed and direction with limited monitoring data.